Senior ETL Engineer

Job Description

The Senior ETL Engineer is responsible for the design, development, optimization, and long-term stewardship of enterprise data pipelines, data warehouse, and lakehouse solutions that support reporting, analytics, and advanced data use cases. This role goes beyond individual pipeline delivery, providing technical leadership, mentorship, and architectural collaboration across the data warehousing function.

The Senior ETL Engineer partners closely with business stakeholders, data scientists, analysts, and BI teams to ensure data products are reliable, scalable, secure, and aligned with business strategy. This role plays a critical part in shaping data standards and ensuring the quality and integrity of enterprise reporting data. Key customers include data science, analytics, and marketing teams operating across marketing, operations, customer insights, and finance.

Senior ETL Engineer Job Duties:

Data Engineering

• Design, build, and maintain scalable, high-performance ETL/ELT pipelines supporting analytics, reporting, and advanced data use cases
• Define and enforce data engineering standards, best practices, and reusable patterns for pipeline development
• Lead data modeling efforts to ensure datasets are optimized for analytics, performance, and usability
• Evaluate and recommend improvements to existing data architectures, tools, and processes to support growth, scalability, and cost efficiency
• Leverage AI tools responsibly to improve ETL development productivity and quality, including accelerating pipeline development, test generation, documentation, anomaly detection, and operational troubleshooting

Data Quality, Reliability & Operations

• Establish and enforce data quality, validation, fault-tolerance, and automated testing frameworks across all pipeline stages
• Ensure data integrity, accuracy, freshness, and lineage throughout the data lifecycle

DataOps, Automation & Optimization

• Lead DataOps and CI/CD practices for data pipeline deployment and management
• Drive automation to reduce manual processes in all stages of development
• Continuously optimize pipeline performance through query tuning, architectural improvements, and technology enhancements
• Identify and eliminate waste in data flows, reducing redundant processing and improving overall efficiency
• Evaluate, test, and adopt new tools, platforms, processes, and solutions aligned with modern data engineering best practices

Leadership & Mentorship

• Serve as a technical lead for complex or high-impact data initiatives
• Mentor and coach ETL Engineers, and collaborate on data architecture evolution
• Share knowledge through documentation, design artifacts, and technical guidance

Collaboration & Stakeholder Engagement

• Partner with business stakeholders to understand business requirements and translate into scalable data solutions
• Lead technical discussions to resolve ambiguous or competing data needs
• Communicate complex concepts clearly to technical and non-technical audiences
• Collaborate with data scientists, analysts, and BI engineers to adopt data products, and improve data usability and trust
• Act as a trusted advisor on data feasibility, trade-offs, risks, and prioritization

Security, Governance & Compliance

• Ensure data pipelines adhere to enterprise security, privacy, and governance standards
• Implement access controls, data protection measures, and compliance requirements
• Support data lineage, auditability, and metadata management initiatives