Senior Data Engineer (in person)

Job description

**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 - 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 - 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 - 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) - Must be legally authorized to work in the United States - Must not require visa sponsorship or have work authorization based on OPT or CPT - Must be able to work from our office in Westfield, IN without relocation financial assistance