Overview
Skills
Job Details
Lead Data Engineer
W2 Candidates (with minimum validity of 12 months)
Pennington, NJ (Hybrid)- Look for nearby candidates
Description:
• We are seeking an experienced and results-driven Data Technology Leader to lead enterprise-scale data initiatives.
• This role requires strong technical expertise in data preparation, orchestration, and integration, combined with leadership skills to manage multiple scrum teams and deliver major rollouts.
• The ideal candidate will have hands-on experience with modern data tools, workflow automation, and architecture design for large-scale projects.
Key Responsibilities:
• Lead multiple scrum teams to deliver enterprise-level data solutions and architecture.
• Administer and manage data preparation tools such as Alteryx, RapidMiner, and Tableau Prep.
• Design, optimize, and tune SQL/PL-SQL queries for high performance.
• Develop and maintain Python-based solutions for data processing and automation.
• Implement and maintain CI/CD pipelines across multiple environments.
• Mentor development teams on best practices for performance optimization and code quality.
• Troubleshoot and resolve performance issues, ensuring scalability and reliability.
• Collaborate in a shared services environment to support cross-functional initiatives.
Required Qualifications:
• Hands-on experience with workflow orchestration for data-driven solutions.
• Expertise in optimizing data integration pipelines using ETL tools.
• Strong knowledge of task dependency tuning and scheduling for scalability.
• Proficiency with OpenShift containers and containerized deployments.
• Experience with Airflow or similar batch processing tools.
• Solid understanding of CI/CD automation and pipeline management.
• Ability to lead large-scale architecture initiatives and enterprise rollouts.
Desired Skills:
• Familiarity with Operational Insights (preferred).
• Experience in ETL automation and orchestration.
• Strong Python programming and scripting skills.
• Ability to mentor and guide teams in best practices.
• Exposure to shared services environments and enterprise-level governance.