Data Engineer II

In this implementation-focused role, you will design, build, test, troubleshoot, and optimize reliable data solutions. You will collaborate with data, analytics, platform, and business stakeholders to reproduce trusted reporting capabilities while advancing reusable enterprise standards.

• Deliver end-to-end data and analytics capabilities, including data modeling, ingestion, transformation, orchestration, testing, and production support.
• Develop scalable, secure, observable, and fault-tolerant workflows using SQL, Python, PySpark, Snowflake, dbt, Airflow, Spark, and AWS services.
• Build and maintain Bronze, Silver, and Gold layer transformations aligned with medallion architecture and enterprise star-schema standards.
• Support onboarding and integration of strategic platforms using reusable integration patterns.
• Create source-to-enterprise mappings and contribute to canonical data models, semantic definitions, and reusable Gold-layer data products.
• Reproduce and validate existing extracts, reports, and datasets by reconciling new platform outputs against current production outputs.
• Implement automated data quality controls, monitoring, alerting, scorecards, and reusable testing libraries across data platform layers.
• Analyze source systems, client data, and business requirements to determine solution feasibility and translate needs into maintainable technical designs.
• Document issues, designs, lineage, solutions, findings, and recommendations clearly for internal and external stakeholders.
• Use AI-assisted engineering capabilities responsibly to build, debug, test, improve productivity, and accelerate delivery while maintaining review and quality standards.