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Materials Data Specialist

Radiant is seeking a Materials Data Specialist to support the development of our internal materials database. This role focuses on researching, validating, and organizing material property data used by engineering teams across reactor design, thermal systems, and structural analysis.

The ideal candidate has a technical background in materials science, materials engineering, or a related engineering discipline and enjoys working at the intersection of engineering research, data quality, and structured documentation.

You will evaluate the quality of material property sources, organize data into defined schemas, and contribute to documentation that helps engineers confidently use materials data in design and analysis.

Responsibilities

Research Materials Data

• Search scientific literature, databases, and reports to identify relevant material property data.
• Evaluate the quality, reliability, and applicability of material property sources.
• Flag inconsistencies or uncertainty in data sources.

Structure Engineering Data

• Enter material property data into internal databases following defined schemas and standards.
• Maintain consistent formatting and traceability of data sources.
• Ensure data integrity and reproducibility for engineering use.

Document Materials Information

• Write concise descriptions of materials and their properties in supporting reports.
• Summarize relevant test conditions, limitations, and assumptions for engineering teams.
• Maintain clear documentation of data sources and methodologies.

Interested in helping build the next phase of hyperscale data center expansion?

BlueSky Resource Solutions is partnering with a leading infrastructure services provider who is seeking a Regional Director of Data Center Infrastructure to oversee delivery operations within a major hyperscale market.

This role will lead ISP deployments within data center environments while building operational processes, developing field teams, and ensuring high levels of client satisfaction.

The ideal candidate is a hands-on operational leader with experience managing complex infrastructure projects, supporting business growth, and maintaining strong safety, quality, and financial performance standards.

Your project direction:

• Provide leadership for structured cabling and inside plant (ISP) infrastructure projects within large-scale data center environments.
• Oversee project lifecycle activities including planning, staffing, scheduling, quality control, and final project turnover.
• Build and lead field teams including supervisors, technicians, and project support staff.
• Develop and implement operational standards, documentation practices, testing procedures, and installation guidelines aligned with industry standards.
• Maintain strong relationships with enterprise and hyperscale data center customers, ensuring service-level commitments and project milestones are met.
• Collaborate with construction partners, electrical contractors, and facility operations teams to coordinate infrastructure deployment.
• Monitor project financials including labor forecasting, materials planning, change management, and cost control.
• Identify opportunities to improve operational efficiency through standardized processes, prefabrication, and digital reporting tools.

The best fit:

• 8+ years of experience in data center infrastructure, structured cabling, or network deployment environments.
• Experience managing field teams and overseeing multiple projects.
• Demonstrated experience managing project budgets, scheduling, and operational performance metrics.
• Strong client-facing communication and leadership capabilities.
• Industry certifications are considered a plus.
• Ability to meet site access requirements including background screening and safety compliance.

Job Overview:

We are seeking a Data Engineer to support data pipeline development and ETL processes.

Responsibilities:

Build and maintain ETL pipelines

Optimize database performance

Work with structured and unstructured data

Ensure data integrity

Requirements:

Degree in Data Engineering or related field

Knowledge of SQL, Python

Familiarity with data warehousing concepts

Sr Data & BI Engineer (Hybrid)

We're partnering with a growing organization seeking a SQL-focused Data & BI Engineer to build and optimize data pipelines, support ETL processes, and drive reporting infrastructure. This role sits at the intersection of data engineering and business intelligence, with strong visibility across teams and leadership.

What You'll Do

• Design, build, and maintain SQL-based data pipelines and transformations
• Develop and optimize ETL processes to support reporting and analytics
• Write performant SQL for data modeling, transformation, and downstream consumption
• Support and enhance reporting infrastructure (SSRS → Power BI migration)
• Partner with business and technical teams to deliver scalable data solutions
• Improve data quality, structure, and accessibility across systems
• Contribute to performance tuning and optimization of data workflows

What You Bring

• Strong SQL skills with experience in data transformation and pipeline development
• Experience with ETL tools or frameworks (SSIS or similar)
• Exposure to BI tools such as Power BI or SSRS
• Experience working with structured data models in a production environment
• Ability to operate across both data engineering and reporting use cases

Environment

• Hybrid: 3 days onsite
• Evolving data environment with active investment in modernization
• Transitioning reporting stack from SSRS to Power BI
• Collaborative team with dedicated DBA support

Compensation

$120K – $140K base + bonus potential and good benefits

Job Title: Senior Data Engineer

Location: Chicago, IL (Hybrid)

Department: Data & Analytics

Reports To: Head of Data Engineering / Data Platform Lead

Role Overview

We are seeking a highly skilled Senior Data Engineer with strong Python development expertise and deep experience in Snowflake to design, build, and optimize scalable enterprise data solutions. This role is based in Chicago, IL and will support regulatory and risk data initiatives in a highly governed environment.

The ideal candidate has hands-on experience building modern cloud data platforms and is familiar with risk management frameworks, BCBS 239 principles, and Governance, Risk & Compliance (GRC) requirements within financial services.

Key Responsibilities

Data Engineering & Architecture

Design, develop, and maintain scalable data pipelines using Python.

Build and optimize data models, transformations, and data marts within Snowflake.

Develop robust ELT/ETL frameworks for structured and semi-structured data.

Optimize Snowflake performance, cost efficiency, clustering, and workload management.

Implement automation, monitoring, and CI/CD for data pipelines.

Risk & Regulatory Data Management

Support regulatory reporting aligned with BCBS 239 (risk data aggregation and reporting).

Ensure data traceability, lineage, reconciliation, and auditability.

Implement controls aligned with Governance, Risk & Compliance (GRC) frameworks.

Partner with Risk, Finance, Compliance, and Audit teams to deliver accurate and governed data assets.

Data Governance & Quality

Develop and enforce data quality validation frameworks.

Maintain metadata, lineage documentation, and data catalog integration.

Implement data access controls and security best practices.

Technical Leadership

Provide mentorship and code reviews for data engineering team members.

Promote engineering best practices and documentation standards.

Collaborate cross-functionally with architects, analysts, and business stakeholders.

Required Qualifications

7+ years of experience in Data Engineering or Data Platform development.

Strong Python programming expertise (Pandas, PySpark, Airflow, etc.).

Hands-on experience with Snowflake (data modeling, Snowpipe, Streams & Tasks, performance tuning).

Advanced SQL skills and deep understanding of data warehousing concepts.

Experience supporting BCBS 239 compliance or similar regulatory reporting frameworks.

Experience working within Governance, Risk & Compliance (GRC) structures.

Experience in cloud environments (AWS, Azure, or GCP).

Strong understanding of data lineage, controls, reconciliation, and audit requirements.

Preferred Qualifications

Experience in banking, capital markets, or financial services.

Knowledge of credit risk, market risk, liquidity risk, or regulatory reporting domains.

Experience with data governance tools (Collibra, Alation, etc.).

Familiarity with DevOps practices, Docker, Kubernetes.

Experience building enterprise data platforms in highly regulated environments.

Key Competencies

Strong problem-solving and analytical thinking.

Ability to operate in a regulated, audit-driven environment.

Excellent communication and stakeholder management skills.

Detail-oriented with a focus on data accuracy and integrity.

Leadership mindset with hands-on technical capability.

*At Securian Financial the internal position title is Data Science Sr Con.*

Position Overview

As a Lead Data Scientist at Securian Financial, you are a recognized expert and technical leader within the organization. You will apply deep analytical and machine learning expertise to solve complex enterprise problems while shaping the technical direction of data science and AI initiatives. You seek to understand first, build scalable solutions that drive strategic growth and value, and thrive in a collaborative, teamwork-oriented environment.

You will play a key role in advancing our enterprise AI and advanced analytics capabilities, influencing tooling standards, MLOps practices, and responsible AI adoption across the organization. Our company values innovation, collaboration, and excellence, and we offer a supportive and inclusive environment where diverse perspectives are encouraged and professional growth is prioritized.

Key Responsibilities

• Design, develop, and productionize advanced machine learning and AI models in partnership with data engineering and software engineering teams.

• Establish and promote MLOps best practices, including experiment tracking, model versioning, reproducibility, CI/CD, and model monitoring using tools such as MLflow and DSpy.

• Lead the design and evaluation of AI and generative AI solutions, including LLM-based systems, and agent-based workflows.

• Collaborate with cross-functional team to identify, prioritize, and deliver high-impact, data-driven solutions.

• Communicate complex analytical and model-driven insights to technical and non-technical audiences through clear narratives, reports, and presentations.

• Ensure model quality, robustness, and regulatory alignment through rigorous testing, validation, and explainability techniques.

• Drive adoption of enterprise standards for data science, machine learning, and responsible AI.

• Identify opportunities for process improvements and automation using advanced analytics and AI techniques.

• Lead and mentor more junior data scientists, providing guidance and support in their professional development while working on projects.

Preferred Qualifications

• A Master's or PhD degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

• At least 5 years of experience in data science or a related field, with a minimum of 2 years in a project leadership role.

• Experience building and deploying production solutions

• Experience with MLOps tools and practices, including MLflow (or similar) for experiment tracking and model management.

• 2+ years of experience in Insurance, actuarial, or a related field

• Proficiency in programming languages such as Python

• Strong expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).

• Solid understanding of statistical analysis, data visualization, data wrangling techniques, NLP approaches, ML model selection.

• Solid understanding of model approaches to satisfy regulatory requirements regarding explainability/interpretability of advanced AI/ML models

• Excellent problem-solving skills and the ability to think critically and analytically.

• Strong communication and presentation skills, with the ability to convey complex concepts to non-technical audiences.

• Demonstrated ability to manage multiple projects and prioritize tasks effectively.

• A passion for continuous learning and staying current with industry trends and developments.

Preferred Skills

• Experience with natural language processing (NLP), LLMs, prompt engineering, and advanced ML models.

• Familiarity with modern ML debugging, evaluation, and optimization tools such as DSpy or equivalent.

• Knowledge of responsible AI practices, including bias detection, fairness assessment, and model risk management.

• Knowledge of data governance and data privacy regulations.

• Background in finance, healthcare, or other specialized industries.

#LI-hybrid **This position will be in a hybrid working arrangement.**

Securian Financial believes in hybrid work as an integral part of our culture. Associates get the benefit of working both virtually and in our offices. If you're in a commutable distance (90 minutes), you'll join us 3 days each week in our offices to collaborate and build relationships. Our policy allows flexibility for the reality of business and personal schedules.

The estimated base pay range for this job is:

Pay may vary depending on job-related factors and individual experience, skills, knowledge, etc. More information on base pay and incentive pay (if applicable) can be discussed with a member of the Securian Financial Talent Acquisition team.

Be you. With us. At Securian Financial, we understand that attracting top talent means offering more than just a job - it means providing a rewarding and fulfilling career. As a valued member of our high-performing team, we want you to connect with your work, your relationships and your community. Enjoy our comprehensive range of benefits designed to enhance your professional growth, well-being and work-life balance, including the advantages listed here:

Paid time off:

• We want you to take time off for what matters most to you. Our PTO program provides flexibility for associates to take meaningful time away from work to relax, recharge and spend time doing what's important to them. And Securian Financial rewards associates for their service by providing additional PTO the longer you stay at Securian.

• Leave programs: Securian's flexible leave programs allow time off from work for parental leave, caregiver leave for family members, bereavement and military leave.

• Holidays: Securian provides nine company paid holidays.

Company-funded pension plan and a 401(k) retirement plan: Share in the success of our company. Securian's 401(k) company contribution is tied to our performance up to 10 percent of eligible earnings, with a target of 5 percent. The amount is based on company results compared to goals related to earnings, sales and service.

Health insurance: From the first day of employment, associates and their eligible family members - including spouses, domestic partners and children - are eligible for medical, dental and vision coverage.

Volunteer time: We know the importance of community. Through company-sponsored events, volunteer paid time off, a dollar-for-dollar matching gift program and more, we encourage you to support organizations important to you.

Associate Resource Groups: Build connections, be yourself and develop meaningful relationships at work through associate-led ARGs. Dedicated groups focus on a variety of interests and affinities, including:

• Mental Wellness and Disability

• Pride at Securian Financial

• Securian Young Professionals Network

• Securian Multicultural Network

• Securian Women and Allies Network

• Servicemember Associate Resource Group

For more information regarding Securian's benefits, please review our Benefits page.

This information is not intended to explain all the provisions of coverage available under these plans. In all cases, the plan document dictates coverage and provisions.

Securian Financial Group, Inc. does not discriminate based on race, color, religion, national origin, sex, gender, gender identity, sexual orientation, age, marital or familial status, pregnancy, disability, genetic information, political affiliation, veteran status, status in regard to public assistance or any other protected status. If you are a job seeker with a disability and require an accommodation to apply for one of our jobs, please contact us by email at , by telephone (voice), or 711 (Relay/TTY).

To view our privacy statement click here

To view our legal statement click here

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• Data management
  
• May do some vendor management
  
• Some data presentation
  
• Some process improvement
  
• Data mining to assist operations around lab equipment maintenance
  
• Some vendor management
  

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• As a Client Data Analyst, you will perform basic analysis to ensure that recommendations and business conclusions are backed by thorough data research and findings.
  
• This job is part of the Data Science & Analytics job function. They are responsible for reviewing data that supports improving effectiveness and predicting outcomes to develop business intelligence.
  

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• Coordinate data aggregation and curate reports using existing business intelligence and reporting applications.
  
• Perform ad-hoc, strategic review of structured and unstructured data, reflecting global real estate markets and the operations of real estate assets.
  
• Assist with developing data structures and pipelines to organize, collect, cleanse, and standardize information to generate insights.
  
• Define basic data requirements and gather information using judgment and statistical tests.
  
• Use programming and evaluation tools, including open-source programs to plan models and extract insights.
  
• Apply modeling and optimization methods to improve business performance.
  
• Develop ad-hoc reporting based on the review of existing data sources.
  
• Exhibit rigor, judgment, and ability to present a detailed 'data story' to a business line.
  
• Confirm the quality and integrity of existing data sources.
  
• Collaborate with the agile development team to provide recommendations and communications on enhancing existing or new processes and programs.
  
• Have some knowledge of standard principles with limited practical experience in applying them.
  
• Lead by example and model behaviors that are consistent with Client RISE values.
  
• Impact the quality of own work.
  
• Work within standardized procedures and practices to achieve objectives and meet deadlines.
  
• Exchange straightforward information, ask questions, and check for understanding.
  

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• Bachelor's Degree preferred with up to 3 years of relevant experience. In lieu of a degree, a combination of experience and education will be considered. MCSE and CNE Certification preferred.
  
• Ability to use existing procedures to solve standard problems.
  
• Experience with analyzing information and standard practices to make judgments.
  
• In-depth knowledge of Microsoft Office products. Examples include Word, Excel, Outlook, etc.
  
• Organizational skills with a strong inquisitive mindset.
  

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• Extreme attention to detail
  
• Great with time management and has a sense of urgency to complete tasks
  
• Excellent communication skills
  
• Will need to be able to "tell the story of the data"
  

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• Experience with pharmaceutical equipment management is a huge plus
  
• Vantage experience
  

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• 4-7 years
  

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• Excel
  
• Microsoft Office suit
  
• Vantage
  
• Smart sheets
  

IBM Consulting is seeking an accomplished Data & Analytics Associate Partner to accelerate our growth within the Industrial & Communications sectors. This executive role is responsible for shaping client vision, cultivating senior executive relationships, and developing data-driven solutions that enable clients to successfully navigate complex transformation programs.

You will bring together deep industry expertise and IBM’s portfolio of data, analytics, and AI capabilities to help organizations modernize their data ecosystems—migrating from legacy platforms to modern hybrid cloud architectures—while adopting next-generation analytics, GenAI, and agentic AI to strengthen decision-making and deliver measurable business and financial outcomes.

This role is ideal for a seasoned leader who integrates industry depth, consulting excellence, and technical thought leadership, has a strong understanding of competitive market dynamics, and consistently delivers high-impact transformation at scale.

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• Expand IBM’s Data & Analytics presence by identifying new market opportunities, developing differentiated solutions, and building a strong pipeline.

  
  

• Engage senior client executives to understand strategic priorities and shape data transformation roadmaps aligned to their business and financial goals.

  
  

• Lead end-to-end sales cycles, including solution definition, proposal leadership, financial structuring, and contract negotiation.

  
  

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• Advise C-suite leaders on strategies to their data estate modernization, advanced analytics, GenAI, and agentic AI to drive business performance.

  
  

• Architect integrated solutions that include:

  
  

• Migration from legacy data platforms to modern cloud-based architectures

  
  

• Data engineering and Information governance

  
  

• Business intelligence and advanced analytics

  
  

• GenAI-powered and agentic AI-driven automation and decisioning

  
  

• Lead complex transformation programs from discovery through delivery, ensuring measurable outcomes and client satisfaction.

  
  

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• Oversee multi-disciplinary delivery teams to ensure high-quality, consistent execution across all program phases.

  
  

• Manage engagement financials, including forecasting, margin performance, and overall portfolio profitability.

  
  

• Align right client technologies, industry expertise, and global delivery capabilities to maximize client value.

  
  

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• Recruit, mentor, and grow top-tier consultants, architects, and data specialists.

  
  

• Build and scale capabilities in data modernization, cloud data engineering, analytics, GenAI, and emerging agentic AI techniques.

  
  

• Contribute to practice strategy, offering development, and capability growth across the global Data & Analytics team.

  
  

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• Stay ahead of sector and technology trends, including cloud modernization, GenAI, agentic system design, regulatory changes, and evolving competitive dynamics.

  
  

• Represent IBM at industry conferences, client events, webinars, and executive roundtables.

  
  

• Create original thought leadership—articles, perspectives, point-of-views—that positions IBM as a leading advisor in data and AI-driven transformation.

  
  

This position can be preformed anywhere in the US.

"Leaders are expected to spend time with their teams and clients and therefore are generally expected to be in the workplace a minimum of three days a week, subject to business needs."

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• 12+ years of experience in consulting, data strategy, analytics, or digital transformation, with strong exposure to the Industrial or Communications sectors.

  
  

• Hands-on experience modernizing data ecosystems, including migrating from legacy on-premise platforms to modern cloud-native or hybrid cloud architectures.

  
  

• Deep expertise with major cloud platforms and their data/analytics stacks, including implementation experience with:

  
  

• AWS (e.g., Redshift, S3, Glue, EMR, Athena, Lake Formation, Bedrock, SageMaker)

  
  

• Microsoft Azure (e.g., Azure Data Lake, Synapse, Data Factory, Databricks on Azure, Fabric, Cognitive Services)

  
  

• Google Cloud Platform (e.g., BigQuery, Cloud Storage, Dataflow, Dataproc, Vertex AI)

  
  

• Experience designing and implementing end-to-end data pipelines, governance frameworks, and analytics solutions on one or more of these platforms.

  
  

• Strong understanding of GenAI architectures, LLM integration patterns, vector databases, retrieval-augmented generation (RAG), and emerging agentic AI frameworks.

  
  

• Proven track record of selling, structuring, and delivering large-scale data and AI transformation programs.

  
  

• Robust technical and functional expertise in data engineering, cloud data platforms, analytics, AI/ML, information management, and governance.

  
  

• Executive-level communication and presence, with demonstrated ability to influence senior stakeholders and convey complex topics through compelling narratives.

  
  

• Financial management experience, including engagement economics, forecasting, margin optimization, and portfolio profitability.

  
  

• Demonstrated leadership in building, scaling, and developing high-performing consulting and technical teams.

  
  

IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

About the Company

Our client is a well-established global insurance and financial services organization known for its strong reputation, financial stability, and long-term commitment to innovation. The company is investing heavily in modern technology and data platforms to transform how insurance products are delivered to professionals and small businesses.

Within this organization, a rapidly growing digital product team is focused on simplifying insurance through modern technology, data-driven decision making, and scalable cloud infrastructure. The team operates in a collaborative, fast-paced environment and places a strong emphasis on engineering excellence, ownership, and continuous improvement.

About the Role

Our client is seeking a Senior Data Engineer to join their Platform Engineering team in Boston. This role will play a key part in designing, building, and scaling a modern cloud-native data platform used to support analytics, business intelligence, and data-driven decision making across the organization.

This individual will work closely with engineering leaders, data teams, and business stakeholders to develop scalable data integration pipelines and build the foundation for enterprise analytics. The role is highly hands-on and ideal for someone who enjoys building data platforms, working with cloud technologies, and enabling self-service analytics.

The team operates in an Agile environment and values collaboration, ownership, and continuous improvement.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Azure Data Factory, Databricks, and SQL Server
• Build configuration-driven ingestion processes to support batch and near real-time data pipelines
• Integrate and transform data from multiple sources including APIs, JSON, CSV, XLS, and other structured and semi-structured formats
• Design and document data models, data flows, and data dictionaries to support enterprise analytics
• Implement Lakehouse architecture using Medallion data modeling patterns
• Develop datasets and reporting pipelines supporting Power BI and enterprise analytics
• Maintain the health, security, and scalability of the Azure-based data platform
• Implement best practices for data governance, metadata management, lineage, and access control
• Build and maintain CI/CD pipelines for data infrastructure using tools such as GitHub Actions or CircleCI
• Implement monitoring, alerting, and observability for data pipelines and platform performance
• Optimize data pipelines for performance, scalability, and cost efficiency
• Work cross-functionally with engineering, product, and business teams to define and deliver data products
• Participate in Agile ceremonies including sprint planning, backlog refinement, and delivery cycles
• Mentor junior engineers and contribute to the ongoing development of the data engineering team
• Stay current on emerging technologies and best practices in data engineering

Qualifications

• 7+ years of professional experience in data engineering or data platform development
• Strong experience working in Azure environments, particularly: Azure Data Factory, Databricks, SQL Server / T-SQL
• Experience building scalable ETL / ELT data pipelines
• Experience integrating data from multiple sources including APIs, JSON, XML, CSV, and other formats
• Strong understanding of data warehousing, dimensional modeling, and Lakehouse architecture
• Experience with Power BI, SSRS, or other reporting platforms
• Hands-on experience with CI/CD pipelines and DataOps practices
• Familiarity with data governance, data quality, metadata management, and MDM
• Experience working in Agile development environments
• Strong communication and collaboration skills with the ability to work across technical and business teams
• Experience mentoring or guiding other engineers is a plus