Data Warehouse & Data Integration
Listed on 2026-01-01
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IT/Tech
Data Engineer, Cloud Computing
Technical Lead Data Warehouse & Data Integration
Fulltime
Chicago, IL
Hybrid (2 Days in a week)
Salary $130-160K Base
OverviewWe’re looking for a strong Technical Lead who can guide our data engineering efforts while staying hands‑on. This role is 60% leadership (managing a small onshore/offshore team) and 40% technical delivery. You will drive modernization across our data warehouse, ETL pipelines, and reporting platforms as we move from on‑prem SQL/SSIS toward Azure, Fabric, and modern cloud data solutions.
Key Responsibilities Data Engineering & LeadershipLead a distributed team focused on ETL development, pipelines, and DW loads.
Build and maintain data workflows using SSIS, SQL, Azure Data Factory, Fabric, and Python/Databricks (nice to have).
Support on‑prem SQL Server/SSRS and cloud platforms like Redshift and Microsoft Fabric.
Stay hands‑on‑coding, debugging, reviewing, and contributing directly.
Manage sprints, backlog, and progress using Scrum and JIRA.
Own end‑to‑end delivery from requirements through deployment.
Identify risks, remove blockers, and ensure quality and timelines.
Define and enforce clean architecture and data standards.
Lead efforts around data validation, cleansing, and transformation.
Introduce frameworks or tooling to improve data quality and observability.
Work closely with Product Owners, Architects, Analysts, and Business Leaders.
Communicate roadmaps, delivery plans, and updates to stakeholders.
Partner with BI and DBA teams to align reporting, modeling, and infrastructure.
Drive the transition to modern, cloud‑first DW/ETL solutions.
Support evaluation and implementation of tools such as Fabric, Synapse, Redshift, Terraform.
Explore automation/AI tooling to improve pipeline reliability and speed.
Bachelor’s degree in CS, IS, or equivalent work experience.
7‑10 years in data warehousing; 3+ years in technical leadership.
Strong SQL, ETL, and data warehousing experience (SSIS, ADF or similar).
Experience with cloud data platforms (Azure, AWS, Google Cloud Platform) and Redshift or SQL Server.
Hands‑on experience with Python (plus), Power BI/SSRS, and Agile/Scrum.
Strong communication, ownership, and ability to lead delivery.
Experience with Fabric, Big Query, Databricks, or other modern data platforms.
Familiarity with Dev Ops/CI‑CD for data pipelines.
Knowledge of data governance, security, and Data Ops practices.
Experience with retail or e‑commerce analytics.
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