Senior Data Engineer – 12-Month Contract

📍 Remote (ET or CT time zones) 🚫 Direct applicants only — we do not work with third parties or vendors. We’re looking for a Senior Data Engineer who’s ready to lead cloud-native, Azure-based data engineering initiatives while shaping modern Lakehouse patterns across the organization. This role is ideal for someone who blends deep hands-on engineering skills with architectural thinking—and wants to influence platform standards, reusable patterns, and technical direction. You’ll design and build end-to-end ingestion pipelines, optimize PySpark/Spark transformations, drive Microsoft Fabric adoption, and architect scalable Lakehouse solutions that support high-volume data processing across the enterprise. What You’ll Do • Design and deliver end-to-end data pipelines using Azure Data Factory, Synapse, and Microsoft Fabric • Build high-performance PySpark/Spark transformations using best practices for partitioning, joins, file sizing, and incremental patterns • Develop API-heavy ingestion frameworks, including REST/SOAP authentication, throttling, retries, and robust error handling • Architect solutions across Azure Data Lake / OneLake, Lakehouse (Bronze/Silver/Gold), and warehouse layers • Provide architectural input and help define platform standards, integration patterns, and target-state roadmaps • Implement monitoring, logging, alerting, runbooks, and support operational triage and RCA • Apply governance, lineage, access controls, and data quality best practices • Write complex SQL, design data models, and support downstream analytics with curated datasets • Drive engineering excellence: reusable patterns, code reviews, documentation, CI/CD, and DevOps alignment What You Bring • 5+ years of data engineering with a strong focus on Azure • Deep experience with Azure Data Factory, orchestration, parameterization, and production operations • Hands-on with Synapse (pipelines, SQL pools and/or Spark) • Advanced PySpark/Spark engineering and performance tuning • Heavy experience with API-based ingestion, including pagination, retries, auth handling, and resiliency • Strong SQL and data warehousing concepts: dimensional modeling, incremental loads, DQ validation • Solid understanding of Data Lake, Lakehouse, and DW architectures • Ability to troubleshoot, optimize, and support production-grade data pipelines • Strong communication and cross-team collaboration skills Bonus Skills • Experience with Microsoft Fabric (Lakehouse, Warehouse, OneLake, Dataflows, notebooks) • Architecture experience contributing to patterns, design reviews, and governance • Data engineering CI/CD experience using Azure DevOps or GitHub • Knowledge of Power BI and semantic modeling for Lakehouse/Warehouse reporting • Familiarity with data catalog and governance tools (e.g., Microsoft Purview)