Senior Data Engineer We are seeking a
Senior Data Engineer to play a critical role in shaping and scaling our enterprise data platform. This highly visible position combines hands-on engineering expertise with architectural leadership, helping drive the evolution of our Enterprise Data Warehouse (EDW) and modern cloud-based data ecosystem. Reporting to the VP of Data, you will design, build, and optimize data pipelines while establishing technical standards, governance practices, and scalable architecture that support analytics, reporting, and business intelligence across the organization.
What You'll Do - Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, PySpark, and modern cloud-based data technologies.
- Build, optimize, and troubleshoot production data pipelines, data quality issues, and performance bottlenecks.
- Create reusable frameworks, components, and best practices that improve development efficiency across the data engineering team.
- Develop and enhance CI/CD processes, automation capabilities, and DataOps practices to support reliable and secure deployments.
- Own the architecture and technical roadmap of the Enterprise Data Warehouse (EDW) and Lakehouse environment.
- Define and maintain data architecture standards, including data modeling methodologies, governance practices, metadata management, and design documentation.
- Produce architecture diagrams, data flow documentation, and technical specifications that support both technical and business stakeholders.
- Evaluate emerging technologies, tools, and frameworks to improve scalability, performance, and long-term maintainability.
- Collaborate closely with Analytics, Business Intelligence, Data Science, Technology, and business leaders to align data capabilities with organizational priorities.
- Establish and promote best practices related to data governance, security, compliance, access controls, lineage, and data stewardship.
- Lead architecture reviews, provide technical guidance, and mentor fellow engineers in engineering and architectural best practices.
- Support strategic initiatives including data modernization efforts, cloud migrations, and enterprise-scale data transformation projects.
Who You Are The Builder You enjoy rolling up your sleeves and solving complex technical challenges. Whether developing pipelines, optimizing queries, or troubleshooting production issues, you thrive in a hands-on environment.
The Architect You think beyond individual solutions and envision scalable, long-term data platforms that support future business growth. You balance technical excellence with practical execution.
The Strategic Partner You build strong relationships across technical and business teams, helping stakeholders understand data opportunities and make informed decisions.
The Standards Champion You are passionate about governance, quality, security, and consistency, ensuring enterprise data remains trusted, accessible, and reliable.
Qualifications Experience - 8+ years of hands-on data engineering experience building and supporting enterprise-scale data platforms.
- Proven experience designing and implementing cloud-based Enterprise Data Warehouse (EDW) and Lakehouse architecture.
- Strong expertise in Python, SQL, and modern data engineering frameworks and technologies.
- Experience with Databricks, Spark, Delta Lake, Unity Catalog, and related cloud-based data platforms.
- Experience developing ETL/ELT pipelines using tools such as Azure Data Factory, Databricks Workflows, dbt, Airflow, Glue, or similar technologies.
- Demonstrated success implementing CI/CD, DataOps, Infrastructure as Code, and automated testing practices.
- Experience establishing data governance, security, metadata management, and compliance standards.
- Proven ability to influence technical direction and collaborate effectively across cross-functional teams.
- Experience mentoring engineers and supporting technical development within a team environment.
Education - Bachelor's degree required in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
- Master's degree is a plus.
Skills & Abilities - Advanced SQL expertise including query optimization, performance tuning, and complex data transformations.
- Strong programming experience in Python and PySpark.
- Deep understanding of dimensional modeling, Data Vault, Kimball, Inmon, and other enterprise data architecture methodologies.
- Working knowledge of cloud data platforms and services, including Databricks and related analytics ecosystems.
- Familiarity with governance, cataloging, lineage, and data quality tools.
- Strong analytical and problem-solving capabilities.
- Ability to communicate complex technical concepts to both technical and non-technical audiences.
- Excellent written and verbal communication skills.
- Ability to manage multiple priorities and perform effectively in a fast-paced, evolving environment.
Preferred Qualifications - Cloud certifications such as AWS Certified Data Engineer or Databricks Certified Data Engineer.
- Experience with streaming data technologies including Kafka, Event Hubs, Kinesis, or Structured Streaming.
- Experience supporting or leading data warehouse modernization and cloud migration initiatives.
- Exposure to business intelligence platforms such as Power BI, Tableau, or Looker.
Location & Work Environment Remote or hybrid opportunity in our Glen Mills, PA, Tempe, AZ, or Coppell, TX locations.
