Leads enterprise data engineering initiatives by designing scalable data architectures, building and optimizing ETL/ELT pipelines, developing data models, and monitoring pipeline reliability. Oversees large-scale data infrastructure, resolves technical issues, manages stakeholder expectations, collaborates across departments, and mentors engineers through technical guidance and code reviews.
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.
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