Manager Azure Data Engineer – Data Factory / Synapse / Databricks
What you will be doing
- Provide technical leadership and direction across multiple Azure-based data engineering projects.
- Lead and mentor data engineering teams, fostering a culture of technical excellence, accountability, and collaboration.
- Stay hands-on to review design and code, ensuring adherence to development standards, performance optimization, and best practices.
- Design, develop, and maintain data pipelines and ETL processes using Azure Data Factory and Databricks (PySpark).
- Architect and optimize data lake and data warehouse solutions leveraging Delta Lake and Synapse Analytics (serverless).
- Define and maintain data architecture frameworks to ensure scalability, security, and maintainability.
- Drive problem-solving to remove technical and operational barriers throughout the lifecycle of client engagements.
- Ensure all deliverables are of high quality by setting clear development standards, enforcing adherence, and participating in code reviews.
- Collaborate closely with business stakeholders, data scientists, and architects to translate business requirements into scalable, production-ready data solutions.
- Oversee and optimize CI/CD, monitoring, and automation practices across teams.
- Stay updated with emerging Azure ecosystem trends and continuously drive innovation and improvement across delivery teams
- Lead and mentor data engineering teams, fostering a culture of technical excellence, accountability, and collaboration.
- Stay hands-on to review design and code, ensuring adherence to development standards, performance optimization, and best practices.
- Design, develop, and maintain data pipelines and ETL processes using Azure Data Factory and Databricks (PySpark).
- Architect and optimize data lake and data warehouse solutions leveraging Delta Lake and Synapse Analytics (serverless).
- Define and maintain data architecture frameworks to ensure scalability, security, and maintainability.
- Drive problem-solving to remove technical and operational barriers throughout the lifecycle of client engagements.
- Ensure all deliverables are of high quality by setting clear development standards, enforcing adherence, and participating in code reviews.
- Collaborate closely with business stakeholders, data scientists, and architects to translate business requirements into scalable, production-ready data solutions.
- Oversee and optimize CI/CD, monitoring, and automation practices across teams.
- Stay updated with emerging Azure ecosystem trends and continuously drive innovation and improvement across delivery teams