DATA ENGINEERING LEAD

Summary

The Data Engineering Lead serves as a pivotal figure within the IT Services sector, responsible for architecting and overseeing the creation of robust, large-scale data pipelines. This role demands a strategic vision to drive data architecture and engineering initiatives while ensuring seamless data integration and optimization. The position is critical for enabling data-driven decision-making across the organization, requiring a professional who can balance technical depth with the ability to manage complex stakeholder relationships and mentor a high-performing team.

Responsibilities

• Design and implement comprehensive data architecture strategies to support enterprise-wide analytics and operational needs.
• Develop and maintain efficient ETL/ELT processes to facilitate smooth data integration across diverse systems.
• Construct and refine data models to ensure high performance, scalability, and reliability of data assets.
• Establish rigorous monitoring protocols for data pipelines, proactively identifying and resolving troubleshooting issues to minimize downtime.
• Lead team members through mentorship, conduct thorough code reviews, and foster a culture of technical excellence.
• Manage stakeholder expectations and collaborate with cross-functional teams to align data solutions with business objectives.
• Oversee the deployment and optimization of large-scale data pipelines to handle increasing data volumes effectively.

Requirements

Requirements:

• A minimum of 8 to 12 years of professional experience in data engineering or related technical fields.
• Proven expertise in SQL and Python for data manipulation, scripting, and application development.
• Deep understanding of data modeling techniques and strategies for data optimization.
• Strong background in building, deploying, and managing ETL/ELT workflows and data integration solutions.
• Demonstrated ability to monitor complex data pipelines and execute effective troubleshooting procedures.
• Exceptional stakeholder management skills with a track record of successful cross-departmental collaboration.
• Experience in leading teams, providing technical guidance, and conducting peer code reviews.
• Familiarity with the design and implementation of large-scale data infrastructure.