Data Engineer

About the role

Inclusively is partnering with a global professional services company to hire a Data Engineer. Please note: this role is NOT an internal position with Inclusively but with the partner company.

Responsibilities

• Design and maintain high-volume batch ETL pipelines using Python/PySpark on Hadoop
• Own Autosys job scheduling and dependency management for production batch operations
• Modernize legacy Oracle PL/SQL systems into scalable distributed data pipelines
• Build and maintain data quality and reconciliation frameworks
• Collaborate with business, compliance, and analytics teams on SLA-driven deliverables

Requirements

• 4+ years of experience as a Data Engineer in production environments
• 4+ years of hands-on Python and PySpark development for large-scale ETL pipelines
• 4+ years of Oracle PL/SQL and relational database development
• 4+ years working with Hadoop ecosystem (HDFS, Hive, YARN)
• 4+ years of enterprise batch job scheduling using Autosys or equivalent (Control-M, Oozie)
• 3+ years of experience in data warehousing concepts (star/snowflake schema, dimensional modeling)
• 3+ years of experience in data quality and reconciliation framework development
• Experience in Financial Services, Retirement, or Banking domain
• Bachelor's degree in Computer Science, Engineering, or related field

Preferred qualifications

• Experience with Apache Kafka, Sqoop, or streaming data pipelines
• Familiarity with AWS (S3, EMR) or equivalent cloud platforms
• Experience with Apache Airflow or dbt for pipeline orchestration
• Exposure to CI/CD pipelines using Jenkins or Git
• Master's degree in a quantitative or technical discipline
• Experience mentoring junior engineers or leading technical delivery

Schedule

• Clients require people to work onsite 3 days per week onsite with the client in Addison, TX
• 5 days of Time Away are mandated per calendar quarter