Stack Using Array Definition In Data Structure Jobs in Usa

Role : Technical Product Manager ( Data Analytics )

Location - Austin, TX (Onsite) - only Local to Texas (other states don't apply)

Exp Req : 10+

Rate : $55/Hr on W2 Max

Skills Mandatory :

1, Marketing Data Analysis knowledge.

2, KPI and metrics definition on Marketing Data. Mainly for media product.

3, Instrumentation knowledge and through process.

Original JD:

• Key Qualification 7+ years of experience in a Data Visualization, Data Scientist, or Data Analyst role, preferably for a digital subscription business.
• Strong proficiency with SQL-based languages is required. Experience with large-scale data technologies such as Hadoop, PySpark
• Proficiency with data visualization tools such as Tableau, , and/or MicroStrategy for analysis, insight synthesis, data product delivery, and executive presentation.
• You have a curious business mindset with an ability to condense complex concepts and analysis into clear and concise takeaways that drive action.
• Excellent communication, social, and presentation skills with meticulous attention to detail.
• Strong time management skills with the ability to handle multiple projects with tight deadlines and executive visibility.
• Be known for successfully bridging analytics and business teams, with an ability to speak the language of both.

Job Description :

• Build dashboards, self-service tools, and reports to analyze and present data associated with customer experience, product performance, business operations, and strategic decision-making.
• Create datasets, Develop global dashboards, data pipelines, sophisticated security controls, and scalable ad-hoc reporting
• Closely partner with our Data Science team to define metrics, datasets, and automation strategy
• Engage with Product, Business, Engineering, and Marketing teams to capture requirements, influence how our services are measured, and craft world-class tools to support those partners.
• Establish a comprehensive roadmap to communicate and manage our commitments and stakeholder expectations while enabling org-wide transparency on progress.
• Focus on scale and efficiency - create and implement innovative solutions and establish best practices across our full scope of delivery
• Education Minimum of a Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or related field. Technical Product Management

Key Qualifications :

• Experience in a Technical Product Management role, preferably for a digital-media or subscription business.
• Knowledge of Client-Server metrics logging strategies as well as data architecture required for analysis
• Hands-on experience with the end-to-end data lifecycle across petabyte-scale technologies
• Prior experience in a technical role (preferably as a data analyst or engineer), delivering data insights to stakeholders
• Strong experience designing and driving product strategy cross-functionally, collaborating with partners of various technical levels.

Nice to have :

• Experience in data-related programming languages (e.g. SQL, PySpark, Python, or R)

Description :

• Data is our product. We are looking for a self-starting, upbeat individual with excellent communication skills who is passionate about managing and developing critical datasets to maximize Data Science capabilities. You should have a strong interest in driving large-scale data products, engaging with key business stakeholders, and driving critical communications throughout the business.

Stephen

Lead Talent Acquisition Specialist

Email :

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• Set the technical strategy for data engineering solutions and data architecture which includes end to end data pipeline strategy, consumption management, project scoping, and data automation.
  
• Design, develop, and optimize data engineering solutions using Snowflake, DBT, Azure Data Factory, and Alteryx.
  
• Continuously assess and optimize the data engineering technology stack to ensure scalability, performance, and alignment with industry best practices.
  
• Implement best practices for data modeling, ETL/ELT processes, and automation.
  
• Own and maintain the Snowflake data warehouse roadmap and engineering standards.
  
• Lead data project scoping, prioritization, and resource allocation to ensure timely delivery of data engineering solutions.
  
• Ensure data integrity, security, and compliance across all engineering solutions.
  
• Collaborate with IT and rest of data teams to align solutions with enterprise
  
• Establish documentation and governance standards for data engineering workflows ensuring completeness, audit readiness, and traceability in alignment with enterprise architecture.
  
• Directly supervise the Data Architecture & Data Engineering team in accordance with Nicolet's policies and applicable laws. Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance; coaching, mentoring and development planning; rewarding and disciplining employees; addressing complaints and resolving problems.
  

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• Bachelor's degree in Computer Science, Data Engineering, Data Analytics or related field.
  
• 7+ years in data engineering or related data roles required.
  
• 3+ years in leadership or management positions required.
  
• Strong technical expertise in Snowflake, DBT, Azure Data Factory and SQL or like systems.
  
• Familiarity with Alteryx, UiPath, Tableau, Power BI and Salesforce is preferred.
  
• Ability to design and implement scalable data solutions.
  
• Excellent leadership, communication, and organizational skills
  
• Ability to balance hands-on development with team development.
  
• Must be able to work fully in-office. This position does not allow for remote work.
  

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• Medical, Dental, Vision, & Life Insurance
  
• 401(k) with a company match
  
• PT0 & 11 1/2 Paid Holidays
  

• At least 3-year experience as architect for large scale cloud data projects involving minimum 3 technological tracks as mentioned above in hyper scaler platforms.
• Minimum 6 years' expertise in data and analytics area.
• Deep understanding of databases and analytical technologies in the industry including MPP and NoSQL databases, Data Lake, Data Warehouse design, BI reporting and Dashboard development.
• Experience of Data architecture, data governance, data quality standards, and data security practices in at least 2 implementations.
• Experience in customer data models and developing KPIs out of customer data.
• Experience in customer facing roles to provide Solutions for Data use cases.
• Certification in the Cloud based data stack.
• Experience in deployment of a large distributed Big Data Application
• Track record of thought leadership and innovation around Big Data. Solid understanding of Data landscape and related emerging technology.

Technical skills needed:

• Languages – Java, Python, Scala
• AWS – S3, EMR, Glue, Redshift, Athena, Lamda
• Azure – Blob, ADLS, ADF, Synapse, PowerBI
• Google Cloud – Bigquery, DataProc, Looker
• Snowflake
• Databricks
• CDH - Hive, Spark, HDFS, Kafka CDH etc.
• ETL – Informatica/DBT/Mattilion,

Roles & Responsibilities:

• Architect and Design Sales and Marketing data initiatives, demonstrate data architectural knowledge, customer management and innovation
• Delivery of customer Cloud data Strategies for Marketing, aligned with customer's business objectives and with a focus on Cloud Migrations
• Provide leadership in platform migration methodologies and techniques including governance frameworks, guidelines, and best practices.
• Build point of views, thought leadership, solutions for proposals, competency development and mentoring etc.
• Solution Design experience on Data Lake, Data Warehouse, BI, Data Mart and Analytics systems
• Delivery of customer Cloud Strategies, aligned with customer's business objectives and with a focus on Cloud Migration.

Position Summary

The Senior Data Scientist will serve as a technical lead in the development of advanced analytical solutions. This role uniquely combines Generative AI innovation with Six Sigma operational rigor to drive measurable improvements across Spectrum’s network and customer ecosystems. You will not only build models but also optimize the processes they inhabit to ensure maximum ROI and statistical stability.

Key Responsibilities

• Generative AI Strategy: Lead the research and implementation of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to automate complex business workflows and enhance internal knowledge management systems.
• Operational Excellence (Black Belt): Apply DMAIC (Define, Measure, Analyze, Improve, Control) methodology to the data science lifecycle. Identify root causes of operational inefficiencies and deploy AI solutions to mitigate them.
• Advanced Modeling: Build, validate, and deploy high-impact predictive models (Churn, CLV, Propensity) using Python, PyTorch, and Scikit-learn.
• Process Optimization: Utilize Black Belt principles to reduce "waste" in data pipelines, improving model training speed and inference efficiency within Databricks/AWS.
• Stakeholder Storytelling: Act as a bridge between technical AI labs and executive leadership, translating complex neural network outputs into Six Sigma-validated business cases.

Required Technical Skills

• GenAI Stack: Experience with LangChain, LlamaIndex, Vector Databases (Pinecone/Milvus), and fine-tuning open-source models.
• Data Engineering: Expert-level SQL and PySpark for grooming large-scale datasets.
• Statistical Control: Deep understanding of Design of Experiments (DoE), hypothesis testing, and Statistical Process Control (SPC) to monitor model drift and performance.
• MLOps: Proficiency in versioning and deploying models in cloud environments (Azure/AWS).

Education & Certifications

• Education: Master’s or PhD in a quantitative field (Statistics, CS, Engineering).
• Certification: Lean Six Sigma Black Belt or Six Sigma Black Belt(

Experience: 5-7+ years of experience in a data-driven environment with a proven track record of leading AI initiatives

As a Data Steward Senior Analyst, you are part of a team responsible for enabling and supporting compliance with data-related enterprise policies within their domains/business units. You and your team are responsible for identifying critical data and associated risks, maintaining data definitions, classifying data, supporting data sourcing / usage requests, measuring Data Risk Controls, and confirming Data Issues are remediated. You have the opportunity to partner across various business units, technology teams, and product/platform teams to define and implement the data governance strategy, supervising and leading data quality, resolving data/platform issues, and driving consistency, usability, and governance of specific product data across the enterprise.

In addition, this role will play a key part in effectively communicating new and updated data-related policies to the teams responsible for compliance. The individual must be skilled in preparing clear, engaging presentations that translate formal policy language into practical, easy-to-understand guidance and “tell the story” behind the policy requirements. The role will also support the delivery of training sessions, facilitate policy office hours, and serve as a go-to resource for questions related to data governance and retention compliance.

Your Primary Responsibilities may include:

• Assist in identifying data-related risks and associated controls for key business processes. Risks relate to Record Retention (primary), Data Quality, Data Movement, Data Stewardship, Data Protection, Data Sharing, among others.

• Develop training materials and educate organization on Record Retention and Deletion processes and procedures.

• Develop deep understanding of key enterprise data-related policies and serve as the policy expert for the business unit, providing education to teams regarding policy implications for business.

• Collaborate with and influence product managers to ensure all new use cases are managed according to policies.

• Influence and contribute to strategic improvements to data assessment processes and analytical tools.

• Support current regulatory reporting needs via existing platforms, working with upstream data providers, downstream business partners, as well as technology teams.

• Subject matter expertise on multiple platforms.

• Responsible to partner with the Data Steward Manager in developing and managing the data compliance roadmap.

Qualifications include:

• 5 + years of experience in a similar role involved with ensuring compliance with Record Retention and Deletion policies.

• Strong communication skills and ability to influence and engage at multiple levels and cross functionally.

• Intermediate understanding of Data Management and Data Governance concepts (metadata, lineage, data quality, etc.) and prior experience.

• 5+ years of Data Quality Management experience.

• Strong familiarity with data architecture and/or data modeling concepts

• 5+ years of experience with Agile or SAFe project methodologies

• Bachelor’s degree in Finance, Engineering, Mathematics, Statistics, Computer Science or other similar fields.

• Preferred: Experience in Travel Industry.

• Preferred: Knowledge of RCSA (Risk Control Self-Assessment) methodology

Leadership Skills may include:

• Makes Decisions Quickly and Effectively: Drives effective outcome through decision making authority. Displays judgement and discretion in order to ensure deliverables are sufficient to the American Express policy and overall compliance.

• Drives Innovation & Change: Provides systematic and rational analysis to identify the root cause of problems. Is prepared to challenge the status quo and drive innovation. Makes informed judgments, recommends tailored solutions.

• Leverages Team - Collaboration: Coordinates efforts within and across teams to deliver goals, accountable to bring in ideas, information, suggestions, and expertise from others outside & inside the immediate team.

• Communication: Influences and holds others accountable and has ability to convince others. Identifies the specific data governance requirements and is able to communicate clearly and in a compelling way.

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

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

Understanding and improving how we optimize ads through the ads delivery funnel to Pinners is fundamental to Pinterest's long-term success. We're looking for a data scientist to join our team in pushing the boundaries in ads optimization. You will be a key member of an organization of talented data scientists innovating on ads delivery.

What you'll do:

• 
  
• Strategy: Evolve our strategy by working closely with product and engineering leaders to build on past learnings and shape our platform's future.
  
• Experimentation: Improve our experimentation capabilities and tools for assessing our ad delivery system, advise on best practices, identify flaws, and build tools and frameworks for experiment analysis.
  
• Leadership: Lead and mentor peers, improving team output through continuous, candid feedback that recognizes strengths and identifies areas for growth. Be a technical leader for junior data scientists.
  
• Communication: Clearly and concisely communicate complex analytical findings and insights to stakeholders with varying technical backgrounds.
  
• Continuous Learning: Stay informed on the latest developments in data science, causal inference, and advertising technology to drive innovation.
  

What we're looking for:

• 
  
• 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data
  
• Direct involvement in the evaluation, refinement, and deployment of ads optimization models for ads delivery systems.
  
• Proficiency in leveraging large datasets for performance analysis and gap identification.
  
• Proven ability to apply scientific methods to solve real-world problems on web-scale data
  
• Expertise in SQL and Python
  
• Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions
  
• Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams
  
• Experience leading key technical projects and substantially influencing the scope and output of others
  
• Experience in digital ad delivery stacks preferred
  

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.

This role will need to be in the office for in-person collaboration 1 times per week and therefore needs to be in a commutable distance from one of the following offices: San Francisco, CA or Seattle, WA.

Relocation Statement:

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• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-NM4

#LI-REMOTE

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

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.