> Markdown version of [/jobs/ext/176241-data-engineer-in-person](https://www.wearedevelopers.com/jobs/ext/176241-data-engineer-in-person). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer (in person) - **Company:** SEP, INC. - **Location:** Westfield, IN, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Automation of Tests, Microsoft Azure, C Sharp (Programming Language), Code Review, Continuous Integration, Data Validation, Information Engineering, Data Infrastructure, Database Queries, Dimensional Modeling, Github, Python (Programming Language), Cloud Services, Software Construction, Software Engineering, Snowflake, Apache Spark, Microsoft Fabric, Bicep, Data Management, Terraform, Software Version Control, Data Pipelines, Databricks - **Published:** May 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=586f1008eb3dc860 ## About the Role Do you have experience in Workflow management (operations management method)?, * 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 platforms (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 ## Description * 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Back(end) to the Future: Embracing the continuous Evolution of Infrastructure and Code](https://www.wearedevelopers.com/videos/440-back-end-to-the-future-embracing-the-continuous-evolution-of-infrastructure-and-code) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)