Lead Data Engineer
KINGS AUTO SALES
Cincinnati, United States of America
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
$ 167KJob location
Cincinnati, United States of America
Tech stack
Azure
Big Data
Software Quality
Code Review
Data Validation
Information Engineering
Data Infrastructure
ETL
Data Transformation
Data Warehousing
Python
Performance Tuning
SQL Databases
Data Processing
Netezza
Spark
PySpark
Ibm Netezza
Data Lakehouse
Data Pipelines
Databricks
Job description
- Lead onshore and offshore data engineering teams across mixed vendor groups, including Capgemini and other partners.
- Drive technical delivery for migration from Netezza to Databricks.
- Translate business and architecture requirements into technical designs and engineering tasks.
- Develop and optimize ETL/ELT pipelines, data transformations, and Databricks workflows.
- Guide conversion of legacy Netezza SQL, scripts, and data processing logic into Databricks solutions.
- Ensure code quality, performance tuning, testing, and adherence to engineering best practices.
- Coordinate with architects, project managers, business stakeholders, and vendor teams.
- Provide mentoring and technical direction to junior and mid-level data engineers.
- Participate in code reviews, issue resolution, deployment, and production support.
- Support data validation, reconciliation, cutover planning, and post-migration stabilization.
Requirements
- 8+ years of experience in data engineering, data warehousing, ETL/ELT, or analytics engineering.
- 2+ years of experience leading onshore/offshore engineering teams.
- Strong hands-on expertise with Databricks, Apache Spark, SQL, and Python/PySpark.
- Experience with IBM Netezza or similar legacy data warehouse platforms.
- Experience supporting data platform migration or modernization initiatives.
- Familiarity with GCP and Azure cloud platforms.
- Strong understanding of data pipelines, data lakehouse concepts, and large-scale data processing.
- Experience working with global delivery teams and multiple vendor partners.
- Strong communication, problem-solving, and technical troubleshooting skills.