Data Engineer (in person)

SEP is looking for a data engineer to join our growing data practice and deliver data solutions for our clients. We’ve been helping companies build great software products since 1988 in a wide range of industries and technologies, and more and more of these products are powered by data. Our clients want us to apply the same engineering rigor we bring to software development to their data pipelines and data platforms. You’ll spend your days building, testing, and shipping data systems that real clients depend on. 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 Build and maintain data pipelines and transformations (batch and streaming) Implement data models for analytics use cases Write data quality checks and tests for data pipelines Configure orchestration and workflow tooling to support delivery Implement infrastructure as code for data platforms Investigate and resolve pipeline failures and performance issues Participate in peer code review and contribute to team documentation Communicate progress, blockers, and risks to the team and stakeholders Support client meetings in a technical capacity Key attributes for applicants A passion for great products, software development, and learning Strong SQL skills with working proficiency in Python; experience with Spark, Scala, R, or C# is a plus Practical experience in data pipeline development, ideally in both batch and streaming patterns Understanding of data modeling patterns for analytics (dimensional modeling, normalized data models, lakehouse concepts) Hands‑On experience with at least one cloud data platform (Azure preferred, AWS and GCP experience also valued) Familiarity with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or Redshift Familiarity with orchestration and workflow management (Apache Airflow, Databricks Workflows, Temporal, or similar) Experience writing tests and data quality checks for pipelines Exposure to 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 Applies software engineering best practices to data engineering (source control, automated testing, code review, CI/CD) Comfortable with ambiguity; can clarify requirements through conversation Interest in mentoring and developing less experienced engineers Professional data engineering experience (2+ 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 We are an equal opportunity employer as to all protected groups, including protected veterans and individuals with disabilities. #J-18808-Ljbffr