Sr. Data Engineer
Job Description
Job Title: Data Engineer
Location: 100% Remote
Employment Type: W2 Contract, 6 Month Contract with possibility of extension
Pay Rate: $50.00 – $55.00/hour
Role Overview:
BEPC is seeking a Data Engineer to support our client by designing, building, and optimizing scalable data pipelines and architectures. This role is ideal for a technically strong professional who thrives in a collaborative environment and enjoys working with large datasets, cloud platforms, and modern data technologies to drive business insights.
Key Responsibilities:
- Design, develop, and maintain ETL pipelines for large-scale structured and unstructured data.
- Build and optimize data architectures, models, and database systems for performance and scalability.
- Develop data solutions using cloud platforms (AWS, Azure, or GCP).
- Collaborate with cross-functional teams to translate business needs into technical solutions.
- Ensure data quality, integrity, and security, especially with sensitive datasets.
- Integrate data from multiple sources including databases, APIs, and flat files.
- Support analytics and machine learning initiatives with clean, reliable datasets.
- Troubleshoot and resolve data pipeline and performance issues.
- Document systems, workflows, and processes for maintainability and knowledge sharing.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or related field.
- 3+ years of experience in data engineering or similar roles.
- Strong experience with ETL processes and data pipeline development.
- Proficiency in SQL and Python.
- Experience with Databricks, Apache Spark, or similar big data tools.
- Hands-on experience with cloud platforms (AWS, Azure, or GCP).
- Strong understanding of database design and optimization.
- Experience working with large-scale and distributed data systems.
- Advanced English communication skills.
Preferred Qualifications:
- Experience with real-time data processing or streaming technologies.
- Familiarity with industrial data systems (e.g., PLCs, LabVIEW).
- Exposure to machine learning workflows or data science collaboration.
- Knowledge of data governance and compliance standards.