Senior Data Engineer
Techpoint
Data Science
Bethesda, MD, USA
Posted on Mar 6, 2026
Data is only as powerful as the foundation beneath it. At SEP, we’re building that foundation — and we’re looking for a Senior Data Engineer who’s ready to lead the way.
We’ve been partnering with companies to build software that matters since 1988. From Fortune 100 enterprises to fast-moving scale-ups, our clients depend on us to tackle complexity, deliver with craft, and stay engaged through every stage of the work. Now, we’re growing our data practice — and we want someone who’s as excited about clean, connected, trustworthy data as we are.
What we have to offer
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- Variety on every axis — tools, technologies, market sectors, methodologies
- Flexible, reasonable work schedules
- Extensive opportunities to learn and develop yourself
- A community of friendly, talented, and effective peers
- Opportunities to try out different roles with minimal risk
- Gorgeous facilities
What you’ll be doing
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- Provide technical direction on data engagements and mentor other engineers
- Design and implement data pipelines and transformations (batch and streaming)
- Develop data models for analytics use cases
- Implement data quality checks and testing strategies for pipelines
- Configure and manage orchestration and workflow tooling
- Build and maintain infrastructure as code for data platforms
- Translate architectural direction into implementation plans
- Communicate progress, risks, and technical tradeoffs to stakeholders
- Support client meetings in a technical capacity
Key attributes for applicants
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- A passion for great products, software development, and learning
- Expert-level SQL skills with strong proficiency in Python; experience with Spark, Scala, R, or C# is a plus
- Deep expertise in data pipeline development, including batch and streaming patterns
- Solid understanding of data modeling patterns for analytics (dimensional modeling, data vault, lakehouse architectures)
- Experience with cloud data platforms — Azure preferred, AWS experience also valued
- Familiarity with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or Redshift
- Understanding of orchestration and workflow management (Apache Airflow, Databricks Workflows, Temporal, or similar)
- Experience with data quality frameworks and testing strategies for pipelines
- Familiarity with infrastructure as code tooling (Terraform, ARM/Bicep) and CI/CD pipelines (GitHub Actions or similar) is a plus
- Experience with analytics engineering tools like dbt and data catalog tools (Unity Catalog, Microsoft Purview) is a plus
- Ability to evaluate architectural tradeoffs in data systems (OLAP vs. OLTP, batch vs. streaming, warehouse vs. lakehouse)
- Comfortable with ambiguity; can clarify requirements through conversation
- Interest in mentoring and developing less experienced engineers
- Professional data engineering experience (8+ years desired)