Data Engineer Lead (Azure Databricks)
Summary
Lead Data Engineer designing and delivering scalable data architectures, pipelines, and models using Azure Databricks, dbt, and SQL while mentoring engineers and enforcing CI/CD and data quality best practices.
We are looking for an experienced Data Engineer Lead to join our team. This role will provide technical leadership in designing and delivering scalable enterprise data and analytics solutions while mentoring engineers and driving best practices across the team.
Key Responsibilities
- Design and implement scalable data architectures, pipelines, data models, and semantic layers using Azure Databricks, dbt, and SQL.
- Lead the development and optimization of complex ELT/ETL workflows, ensuring performance, reliability, security, and scalability.
- Provide technical leadership through architecture reviews, code reviews, and mentoring Junior and Mid-Level Data Engineers.
- Lead the technical delivery of end-to-end data and analytics initiatives.
- Partner with business and technical stakeholders to translate requirements into effective data engineering solutions.
- Establish and promote best practices in data engineering, CI/CD, Git version control, testing, and data quality.
- Contribute to the organization's enterprise data and analytics strategy.
Qualifications
- 5+ years of experience in Data Engineering or related roles, including experience leading technical projects and mentoring engineers.
- Strong expertise in SQL, Azure Databricks, dbt, ELT/ETL, and data modeling.
- Experience designing and delivering scalable cloud-based data and analytics solutions.
- Knowledge of Power BI and semantic modeling is preferred.
- Experience with CI/CD, Git, automated testing, and data engineering best practices.
- Strong communication, collaboration, and stakeholder management skills.
- Relevant certifications in Azure Data Engineering, Databricks, or dbt are an advantage.