We are looking for an experienced, hands-on data Engineering team lead with deep technical expertise for a key role in a dynamic project and consulting environment.
This role is ideal for someone who combines strong professional and technical authority, the ability to lead people and projects, and the mental flexibility to seamlessly switch between different domain areas, clients, and technological challenges.
Professional & Technical Leadership: Lead a team of data Engineers.
Databricks Focus: Extensive work with Databricks, leading platform-based solutions.
Technical Decision-Making: Make key architectural decisions and provide expert guidance to teams, clients, and stakeholders.
Design & Architecture: Perform design and architecture for complex data solutions
Pipeline & Platform Management: Lead data Engineering processes including data pipelines, ETL /ELT workflows, integrations,
Requirements:
5-7+ years of experience in data Engineering, with significant experience in a Senior / Tech Lead / team lead role.
Proven experience with Databricks, dbt, or Snowflake (Strong preference for Databricks).
Hands-on experience in designing and building data pipelines and ETL /ELT processes.
Strong proficiency in Python and SQL.
Deep knowledge of modern data architectures.
Cloud Experience: Practical experience with Azure, AWS, or GCP.
Big Data & Distributed Processing: Hands-on experience with Big Data technologies, specifically Apache Spark / PySpark.
Architecture Advantage: Experience with Delta Lake / Lakehouse architecture (Major advantage).
Leadership Experience: Proven track record in professional/technical leadership of data Engineers.
Project Leadership: Experience leading end-to-end technical projects (Major advantage).
Consulting/Agency Background: Experience in a consulting firm
5-7+ years of experience in data Engineering, with significant experience in a Senior / Tech Lead / team lead role.
Proven experience with Databricks, dbt, or Snowflake (Strong preference for Databricks).
Hands-on experience in designing and building data pipelines and ETL /ELT processes.
Strong proficiency in Python and SQL.
Deep knowledge of modern data architectures.
Cloud Experience: Practical experience with Azure, AWS, or GCP.
Big Data & Distributed Processing: Hands-on experience with Big Data technologies, specifically Apache Spark / PySpark.
Architecture Advantage: Experience with Delta Lake / Lakehouse architecture (Major advantage).
Leadership Experience: Proven track record in professional/technical leadership of data Engineers.
Project Leadership: Experience leading end-to-end technical projects (Major advantage).
Consulting/Agency Background: Experience in a consulting firm
This position is open to all candidates.
