Senior ETL Engineer

WorldStrides•Vienna, VA

1d•$100,000 - $150,000

About The Position

The Senior ETL Engineer designs, builds, and stewards enterprise data pipelines, lakehouse, and warehouse solutions that support reporting, analytics, and advanced data use cases. The role follows an AI-first engineering approach: AI agents assist with execution tasks such as code generation, test scaffolding, documentation, and troubleshooting, while the engineer owns design, specifications, review, and validation. AI is also used as a partner for architecture, trade-off analysis, discovery, and root-cause analysis, with the engineer applying judgment about when AI is appropriate and holding its output to the same standards as human-produced work. The engineer partners with business stakeholders, analysts, and BI teams from problem framing through delivery. They engage stakeholders early to explore possibilities, clarify and shape requirements, and balance consultation with timely delivery. The position contributes to data engineering standards, data modeling, data quality and reliability, DataOps, automation, pipeline optimization, security, governance, and team knowledge-sharing. It also leads complex initiatives as assigned and mentors ETL Engineers, including in effective and responsible AI-assisted workflows.

Requirements

Advanced experience with SQL, relational databases, and data warehouse design.
Strong expertise with Microsoft Fabric and modern data platform concepts.
Proficiency in Python for ETL development, automation, and testing.
Deep understanding of data modeling, query optimization, and performance tuning.
Strong knowledge of DataOps, CI/CD, and automated testing for data platforms.
Experience designing and supporting production-grade, enterprise-scale pipelines.
Hands-on production experience with AI coding assistants and agentic development tools, plus familiarity with MCP and agent tool integration.
A track record of delivering faster with AI without sacrificing quality; examples of work are welcome.
Working knowledge of the AI tooling landscape sufficient to make pragmatic choices without chasing every new model or tool.
Strong code review skills, especially in identifying subtle logic, security, and performance issues in generated code.
Experience engaging stakeholders early to shape requirements, rather than only executing against existing requirements.
Excellent verbal, written, and interpersonal communication skills.
Proven ability to lead multiple initiatives and influence without formal authority.
At least 5 years of experience in data engineering, BI development, or analytics engineering.
Bachelor's degree in a technical or analytical discipline required.

Nice To Haves

Experience with metadata- or config-driven pipeline frameworks.

Responsibilities

Design, build, and maintain scalable, high-performance ETL/ELT pipelines for analytics, reporting, and advanced data use cases.
Help develop and consistently apply data engineering standards, best practices, and reusable patterns in partnership with the data architect and senior engineers.
Lead data modeling efforts to optimize datasets for analytics, performance, and usability.
Evaluate and recommend improvements to data architectures, tools, and processes to support growth, scalability, and cost efficiency.
Use AI coding assistants and agentic tools for pipeline development, configuration, test generation, and documentation; create clear specifications and rigorously review and validate generated work.
Help steward shared AI tooling, including agent skills, reusable prompts, context and convention files, and MCP-connected tooling.
Engage business stakeholders early to explore possibilities, shape requirements, and right-size discovery; use AI to prototype options and turn conversations into draft requirements and follow-up questions.
Offer alternatives and constructively challenge requests when they do not fit the business need, explaining trade-offs in business terms.
Establish and apply data quality, validation, fault-tolerance, and automated testing frameworks across pipeline stages; define expectations and data contracts for testing.
Ensure data integrity, accuracy, freshness, and lineage throughout the data lifecycle; use AI-assisted anomaly detection and troubleshooting while verifying root causes.
Contribute to DataOps and CI/CD practices for data pipeline deployment and management, and drive automation to reduce manual work.
Optimize pipeline performance through query tuning, architectural improvements, and technology enhancements; eliminate redundant processing and other waste in data flows.
Lead complex or high-impact initiatives as assigned, collaborating with the data architect on architecture.
Mentor and coach ETL Engineers, including on writing effective specifications, critically reviewing AI-generated output, and recognizing AI limitations.
Share knowledge through documentation, design artifacts, technical guidance, code reviews, and design discussions.
Lead technical discussions to resolve ambiguous or competing data needs and communicate complex concepts to technical and non-technical audiences.
Collaborate with data scientists, analysts, and BI engineers to improve data-product adoption, usability, and trust.
Build data products that AI agents and AI-assisted analysts can use reliably through well-defined semantic models and query contracts.
Advise stakeholders on data feasibility, trade-offs, risks, and prioritization.
Ensure data pipelines meet enterprise security, privacy, and governance standards; implement access controls, data protection, and compliance requirements.
Apply guardrails to AI and agent usage, including tool permissions, human approval for writes and pipeline execution, and use of sanctioned tools for sensitive customer and financial data.
Support data lineage, auditability, and metadata management initiatives.

Benefits

Comprehensive health benefits, including medical, dental, vision, life, AD&D, accident, critical illness, and disability insurance, plus FSA/HSA options with employer HSA contributions.
Generous 401(k) match.
Paid time off, including 11 paid company holidays, 25 PTO days in the first year (prorated), one paid volunteer day, four mental health days, and bereavement leave.
Professional development support, including up to $5,250 annually for tuition reimbursement and up to $1,000 annually for certifications.
Opportunities for paid and discounted travel.
Flexible work schedule with on-site, remote, and hybrid office opportunities.
Employee Resource Groups.
Employee Assistance Program and wellness resources, including fitness centers at select locations.
Paid parental, caregiver, and disability leave.
Team Member Discount Program.
Engaging, collaborative, and fun work environment.