Data Engineering Team Lead

5 days ago

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Description

• Hands-On Leadership: Act as a player-coach by balancing technical responsibilities with team leadership. Provide mentorship and support for engineers, while also taking development responsibility of key data engineering initiatives. • Data Architecture and Design: Lead the design, development, and deployment of highly scalable and reliable data infrastructure using modern tools like Snowflake, Databricks, and cloud-based services. Continuously refine the data architecture to meet evolving business and technical needs. • ETL and Data Pipelines: Design, build, maintain, and optimize data pipelines and ETL processes using tools like Airbyte and Fivetran for efficient data ingestion, transformation, and storage. Ensure these pipelines are robust, scalable, and production ready. • Collaboration: Work closely with cross-functional teams including data analysts, product managers, software engineers, and business stakeholders to understand data requirements and deliver high-value data solutions. Utilize Looker and PowerBI to provide actionable insights and drive decision-making. • Infrastructure Management: Oversee the management of data infrastructure using modern cloud-based environments (AWS preferred). Implement best practices for infrastructure as code, configuration management, and monitoring (e.g., Terraform, Ansible, Datadog). • Technical Debt Management: Proactively manage and mitigate technical debt within the data platform, balancing the need for innovation with system stability and scalability. • Innovation and Growth: Drive innovation in data engineering by experimenting with new technologies, techniques, and tools. Cultivate a culture of learning and continuous improvement within the team. • Data Governance and Quality: Establish and maintain data governance standards to ensure the integrity, consistency, and accuracy of data. Implement techniques for monitoring data infrastructure reliability and correctness. • Production Operations: Take ownership of the operational reliability of data systems, including on-call support for critical data infrastructure components.

Requirements

• 8+ years of experience as a hands-on data engineer, demonstrating deep technical expertise in building complex, scalable data solutions. • 3+ years of experience leading data engineering teams or initiatives, demonstrating strategic thinking, mentoring, and advising stakeholders. • Bachelor’s degree in Computer Science, Data Science, or a related field.