Senior Data Engineer
About The Position
As a Senior Data Engineer, you will play a critical role in designing, building, and maintaining the data infrastructure that powers analytics solutions across a variety of enterprise client environments. This role combines modern data engineering practices with strong database and data quality fundamentals. You will be responsible for building scalable ETL/ELT pipelines, designing robust data models, integrating data from diverse platforms, and ensuring that every engagement is supported by a reliable, well-documented data foundation. You'll work primarily within Microsoft Fabric environments while collaborating closely with analytics, engineering, and client stakeholders to deliver high-quality, production-ready data solutions. We are looking for someone who takes ownership of data quality, enjoys solving complex integration challenges, and thrives in client-facing consulting environments where every engagement presents a unique set of technical challenges.
Requirements
- 8+ years of professional experience in Data Engineering, Backend Platform Engineering, or large-scale data infrastructure.
- 3+ years of experience in client-facing or consulting-focused data engineering environments.
- Advanced SQL expertise, including schema design, query optimization, complex views, CTEs, window functions, deduplication strategies, and data modeling.
- Strong Python experience for ETL development, automation, PySpark, and data processing workflows.
- Hands-on experience building and maintaining enterprise-scale ETL/ELT pipelines in production environments.
- Experience integrating data from REST APIs, GraphQL endpoints, and webhook-based systems.
- Strong understanding of data quality practices, validation processes, anomaly detection, and data governance.
- Experience working across multiple concurrent client engagements with varying levels of data maturity.
- Excellent documentation and communication skills, including data dictionaries, lineage documentation, and technical handoffs.
- Strong ownership mindset and the ability to operate independently in fast-paced environments.
Responsibilities
- Design, build, and maintain ETL/ELT pipelines for enterprise data ingestion and transformation across multiple client environments.
- Develop and maintain SQL views, schemas, and transformation logic that serve as the foundation for Power BI and other analytics solutions.
- Profile source data before development begins, identifying data quality issues, anomalies, duplicates, null values, and integrity concerns.
- Produce and maintain comprehensive data dictionaries, lineage documentation, and transformation documentation for every engagement.
- Build and manage data pipelines primarily within Microsoft Fabric while supporting Databricks and other client-specific environments as needed.
- Integrate data from REST APIs, GraphQL endpoints, and webhook-based sources, implementing authentication, pagination, rate-limiting, and error handling.
- Implement monitoring, alerting, and refresh processes to proactively identify and resolve pipeline failures.
- Validate data integrity throughout development to ensure reliable and accurate downstream analytics.
- Translate client business requirements into scalable technical data models while identifying limitations and gaps within source systems.
- Collaborate closely with visualization developers to ensure the data layer supports reporting and analytics requirements.
- Create and maintain clear handoff documentation, architecture documentation, and operational runbooks.
- Mentor junior engineers and contribute to engineering best practices, documentation standards, and delivery excellence.
- Participate in engagement planning, solution design, and project execution from kickoff through delivery.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
