Sr. Data Engineer

Architect Next-Gen Lakehouse & AI Infrastructure To maintain strong team cohesion and operational continuity, candidates must CURRENTLY be based in the Greater Chicago Area and commit to a hybrid schedule in the South Suburbs (2 days/week on-site). All applicants must possess unrestricted work authorization in the United States. Please ONLY apply if you meet these criteria so we can stay focused on contact with viable applicants. Thank you! Imagine engineering the data architecture that powers enterprise analytics and AI for a global audience. As a Senior Data Engineer for our client, you won’t just build pipelines—you’ll design, optimize, and scale a multi-cloud data lakehouse that drives real business value. If you’re a cloud‑first data professional ready to own end-to-end ELT systems in AWS and Azure, your next big impact starts here. At-a-Glance Snapshot Location: South Suburd of Chicago / Hybrid-Friendly Impact: High‑visibility infrastructure powering enterprise reporting, D365 ERP, and AI/ML enablement Why Join Our Client? Our client is accelerating its cloud‑first data strategy, transitioning legacy structures into a modern Medallion Lakehouse architecture. You’ll join a collaborative, high‑energy environment where your work directly shapes data governance, system scalability, and advanced analytics. Multi‑Cloud Mastery: Work across both AWS and Azure ecosystems while leveraging cutting‑edge tools like Databricks and Azure Fabric. AI & Analytics Enablement: Lay the foundational data layer for next‑gen AI capabilities (including AWS Bedrock and RAG architectures). High Autonomy & Ownership: Translate complex business requirements into high‑performing, secure technical solutions with minimal friction. Your Impact In this role, you will be the core technical driver of enterprise data solutions. You will: Architect Lakehouse Systems: Build and maintain scalable Medallion‑layer (Bronze/Silver/Gold) lakehouse architectures using AWS and Azure cloud platforms. Engine ELT Pipelines: Design, optimize, and automate robust ETL/ELT pipelines integrating core enterprise platforms like D365 ERP and CRM systems. Power AI & Analytics: Create curated datasets, semantic layers, and high‑quality data feeds that power executive reporting and downstream AI/ML initiatives. Optimize Performance: Fine‑tune complex SQL queries, pipeline orchestration, and cloud storage to ensure high availability and cost efficiency. Drive Governance & Quality: Enforce strict data security, integrity, and compliance standards across structured and unstructured datasets. What You Bring We are looking for a self‑directed engineer who balances technical expertise with a collaborative, business‑first mindset. Experience: 5+ years of hands‑on data engineering or data platform development experience. Cloud Stack: Deep proficiency across AWS (S3, Redshift, Glue, DMS) and Azure (Data Factory, SSIS). Core Competencies: Advanced SQL mastery, relational database design, and proven data modeling skills. Architecture Know‑How: Strong foundational understanding of data warehousing, data lakes, and lakehouse patterns. Education: Bachelor’s degree in Computer Science, Information Systems, or a related technical field. Bonus Points: Experience with Databricks, Spark, Azure Fabric, Power BI, Bedrock/RAG concepts, or CI/CD pipelines in Git/Azure DevOps. Ready to Architect the Future of Data? If you thrive on solving complex data challenges and building scalable cloud solutions, we want to hear from you. #J-18808-Ljbffr