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Lead Data Engineer

  • Job type Posted on: Jul 17, 2026
  • Experience level Anagh Technology
  • Employment type Chicago, Illinois
  • Employment type Onsite
  • Salary Full-time

Job Title :

Lead Data Engineer

Job Type :

Full-time

Job Location :

Chicago Illinois United States

Remote :

No

Jobcon Logo Job Description :

We are seeking a highly experienced Lead Data Engineer to help drive the next evolution of our enterprise data, analytics, and AI ecosystem. In this role, you will lead the design, development, and optimization of a modern AWS + Databricks Lakehouse platform while partnering closely with business and technical stakeholders to deliver scalable, high-performance data solutions. This is a hands-on technical leadership role requiring expertise in data engineering, cloud technologies, ETL/ELT, and modern data architecture. Key Responsibilities Design, develop, and maintain enterprise-grade batch and streaming data pipeline Lead the full ETL/ELT lifecycle from design through deployment and production suppor Build scalable, secure, and high-performance data solutions using AWS and Databrick Drive data engineering best practices, architecture standards, and governanc Optimize Databricks workloads for performance and cost efficienc Implement and manage Delta Lake, Unity Catalog, Delta Live Tables (DLT), Databricks SQL, and workflow orchestratio Collaborate with business stakeholders to translate requirements into scalable technical solution Mentor junior engineers while remaining hands-on with developmen Ensure data quality, reliability, governance, and operational excellenc Participate in Agile ceremonies and contribute to continuous improvement initiative Required Qualifications ns10+ years of IT experience with strong expertise in Data Engineering and ET L.4–6+ years of recent hands-on experience designing and building large-scale data pipeline s.Strong experience wit h:Databric keUnity Catal T)Databricks S QLStrong AWS experience includin g:Amazon S3I AMNetworki ngE C2Expertise in SQL, Python, data modeling, and distributed data processin g.Experience with Lakehouse architecture and Medallion architectur e.Experience with CI/CD, DevOps, and workflow orchestratio n.Strong understanding of Databricks performance tuning and cost optimization, includin ngAuto Scali ngSpot Instanc esPhoton Engine optimizati onExperience designing, configuring, coding, testing, and deploying enterprise data platform s.Strong communication skills with the ability to work directly with business stakeholder s.Experience working in Agile environment Preferred Skills lsLeadership or mentoring experienc e.Strong analytical and problem-solving skill s.Experience supporting enterprise analytics and AI initiative s.Passion for learning new technologies and modern data platform Technical Skills lsDatabric keUnity Catal T)Databricks S QLAWS (S3, IAM, EC2, Networkin g)Pyth onS QLETL / E LTData Modeli ngDistributed Processi ngLakehouse Architectu reMedallion Architectu reCI/ CDDevO psAgi Interview Process ss60–90 minute technical interview focused on architecture, Databricks, AWS, and hands-on desig n.30–45 minute behavioral/team fit interview with the hiring manage #J-18808-Ljbffr

Jobcon Logo Position Details

Posted:

Jul 17, 2026

Reference Number:

14660_3DCC7B089C739437F1429582BA6E5630

Employment:

Full-time

Salary:

Not Available

City:

Chicago

Job Origin:

APPCAST_CPC

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We are seeking a highly experienced Lead Data Engineer to help drive the next evolution of our enterprise data, analytics, and AI ecosystem. In this role, you will lead the design, development, and optimization of a modern AWS + Databricks Lakehouse platform while partnering closely with business and technical stakeholders to deliver scalable, high-performance data solutions. This is a hands-on technical leadership role requiring expertise in data engineering, cloud technologies, ETL/ELT, and modern data architecture. Key Responsibilities Design, develop, and maintain enterprise-grade batch and streaming data pipeline Lead the full ETL/ELT lifecycle from design through deployment and production suppor Build scalable, secure, and high-performance data solutions using AWS and Databrick Drive data engineering best practices, architecture standards, and governanc Optimize Databricks workloads for performance and cost efficienc Implement and manage Delta Lake, Unity Catalog, Delta Live Tables (DLT), Databricks SQL, and workflow orchestratio Collaborate with business stakeholders to translate requirements into scalable technical solution Mentor junior engineers while remaining hands-on with developmen Ensure data quality, reliability, governance, and operational excellenc Participate in Agile ceremonies and contribute to continuous improvement initiative Required Qualifications ns10+ years of IT experience with strong expertise in Data Engineering and ET L.4–6+ years of recent hands-on experience designing and building large-scale data pipeline s.Strong experience wit h:Databric keUnity Catal T)Databricks S QLStrong AWS experience includin g:Amazon S3I AMNetworki ngE C2Expertise in SQL, Python, data modeling, and distributed data processin g.Experience with Lakehouse architecture and Medallion architectur e.Experience with CI/CD, DevOps, and workflow orchestratio n.Strong understanding of Databricks performance tuning and cost optimization, includin ngAuto Scali ngSpot Instanc esPhoton Engine optimizati onExperience designing, configuring, coding, testing, and deploying enterprise data platform s.Strong communication skills with the ability to work directly with business stakeholder s.Experience working in Agile environment Preferred Skills lsLeadership or mentoring experienc e.Strong analytical and problem-solving skill s.Experience supporting enterprise analytics and AI initiative s.Passion for learning new technologies and modern data platform Technical Skills lsDatabric keUnity Catal T)Databricks S QLAWS (S3, IAM, EC2, Networkin g)Pyth onS QLETL / E LTData Modeli ngDistributed Processi ngLakehouse Architectu reMedallion Architectu reCI/ CDDevO psAgi Interview Process ss60–90 minute technical interview focused on architecture, Databricks, AWS, and hands-on desig n.30–45 minute behavioral/team fit interview with the hiring manage #J-18808-Ljbffr

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