Senior Data Engineer

Key Responsibilities

• Own end-to-end design, implementation, and evolution of enterprise data pipelines and core data domains, from source ingestion through analytics and AI-ready datasets
• Architect, develop, and optimize scalable ETL/ELT pipelines integrating multiple internal and external source systems
• Lead the design and optimization of the data lake and data warehouse to support analytics, regulatory reporting, and operational decision-making
• Define and enforce standards for data modeling, testing, deployment, and documentation to ensure long term scalability and maintainability
• Implement and maintain data quality, reliability, and observability practices, including automated testing, monitoring, and alerting
• Establish and support data governance, metadata management, lineage, and role-based access controls in partnership with business and compliance stakeholders
• Design and maintain analytics and ML-ready datasets to support BI, advanced analytics, and future AI/ML initiatives
• Apply DevOps and DataOps best practices, including CI/CD, version control, and environment management for data pipelines
• Troubleshoot and resolve complex data issues involving legacy systems, custom integrations, and evolving business requirements
• Partner closely with Analytics, AI/Data Science, and business leaders to translate complex business and regulatory requirements into robust technical solutions
• Provide technical guidance, code reviews, and best practices to junior data engineers and analysts, contributing to a high-quality data engineering practice (no direct people management)

Experience & Seniority

• Extensive professional experience in data engineering or related roles
• Demonstrated experience owning and operating production-grade data platforms in a cloud environment
• Prominent experience designing and scaling data lakes and data warehouses supporting analytics, reporting, and business critical use cases
• Strong ability to translate complex business and regulatory requirements into reliable, maintainable data solutions
• Experience operating autonomously as a senior individual contributor with accountability for architecture, quality, and delivery
• Senior individual contributor role with no direct people management responsibilities

Technical Skills & Proficiency

• Strong proficiency in Python, including PySpark, for data engineering, automation, and pipeline development
• Expert-level SQL for analytical modeling, performance tuning, and data warehouse optimization
• Deep experience with dbt for transformation, testing, and analytics engineering
• Experience supporting BI tools such as Power BI or similar analytics platforms
• Hands-on experience designing and operating modern cloud data platforms (Snowflake, Databricks, and/or Microsoft Fabric)
• Experience building and managing ELT pipelines using tools such as Fivetran, Airbyte, or equivalent technologies
• Experience implementing data governance, metadata management, lineage, and access controls using tools such as Collibra or Microsoft Purview
• Solid understanding of security, privacy, and access control considerations in enterprise data environments