Senior Data Engineer

🎯 Role Overview

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.

🧩 What you will do

In this role, you will:

• 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.

🧠 What you will bring

We’re looking for someone who has:

• 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.

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