Data Engineer

We’re seeking a skilled Data Engineer to support and enhance a growing Enterprise Data Warehouse (EDW) environment. This role focuses on modernizing ETL frameworks, optimizing large-scale data pipelines, and providing hands-on production support within a collaborative team setting. The ideal candidate will have strong technical proficiency in ETL, SQL, Python, and Linux, along with a passion for data architecture and performance optimization. Key Responsibilities • Design, develop, and modernize ETL pipelines using Apache Spark and Iceberg • Maintain, optimize, and migrate legacy ETL jobs • Integrate mainframe data using Precisely Connect • Participate in an on-call rotation for production support and troubleshooting • Collaborate closely with cross-functional teams, including data engineers, analysts, and administrators • Ensure data quality, consistency, and performance across the data warehouse • Follow SDLC best practices, version control standards, and documentation protocols Requirements Must-Have Qualifications • 3+ years of experience in ETL development or data engineering • Strong proficiency in SQL (complex queries, performance tuning, data modeling) • Hands-on experience with Python and/or Linux scripting in Spark-based environments • Proven production support experience in enterprise data ecosystems • Demonstrated understanding of data architecture and optimization principles • Ability to learn new tools quickly and adapt to evolving data frameworks • Ability to Obtain a Security Clearance Nice-to-Have Skills • Experience with Cloudera (Hive/Impala), Apache Spark, Iceberg, or Airflow • Familiarity with Precisely Connect for Big Data • Background in financial services or student lending data environments • Bachelor’s degree in Computer Science, Data Engineering, or related field (or equivalent experience) Why This Role This is an excellent opportunity to join a team that’s actively modernizing its data environment — leveraging next-generation frameworks and large-scale data platforms. You’ll have the chance to shape a new data warehouse architecture while maintaining the stability of existing pipelines.