Lead Data Engineer

Responsibilities:
Responsible for leading a team of talented data engineers responsible for designing, building, and maintaining scalable data pipelines and infrastructure.
Work closely with cross-functional teams to ensure client data systems meet the highest standards of quality and performance.
Lead, mentor, and develop a team of data engineers, fostering a collaborative and inclusive team environment.
Conduct regular performance reviews, provide feedback, and set goals for team members.
Identify and address skill gaps, and provide opportunities for professional development.
Plan, execute, and deliver data engineering projects on time and within scope.
Coordinate with stakeholders to gather requirements, set priorities, and define project timelines.
Ensure projects align with overall business objectives and data strategy.
Oversee the design, development, and maintenance of data pipelines, ETL processes, and data warehouse.
Ensure data quality, integrity, and security across all data engineering projects.
Identify opportunities for process improvements and drive initiatives to enhance the efficiency and effectiveness of data operations.
Has a strong conceptual understanding of Data Warehousing and ETL, Data Governance and Security, Cloud Computing, and Batch and Real-Time data processing.
Ability to build/drive reusable frameworks that can drive efficiency of the overall data system
Has executed and lead multiple projects, including streaming, batch, large data pipelines, etc.
Manages conversations with the client stakeholders to understand the Internal Use Only requirement and translate it into technical outcomes.
Requirements:
Strong experience with Databricks, Spark, and cloud platforms (Azure, AWS, GCP).
Architect and deploy cloud-based data solutions (Azure, AWS, GCP). Define CI/CD strategies for data pipelines using Terraform, Azure DevOps, or GitHub Actions.
Implement data cataloguing, lineage tracking, and access control (Unity Catalogue, Collibra, Alation).
Ensure compliance with GDPR, CCPA, and industry-specific data security policies.
Develop strategies for distributed computing, parallel processing, and caching mechanisms.

Experience
8-12 yrs