Lead Data Integration Engineer

About the role

We are looking for an experienced Lead Data Integration Engineer to head our data solutions team. In this technical leadership position you will design, build, and maintain enterprise‑grade data pipelines while guiding a high‑performing group of engineers.

Key responsibilities

• Mentor and lead a team of 5+ data integration and ETL engineers, managing sprint planning and risk.
• Conduct code reviews and establish testing frameworks for SQL, Python and Scala code.
• Promote modern software practices such as CI/CD, Git version control, modular design, and automated monitoring.
• Architect end‑to‑end ETL/ELT pipelines using serverless or hybrid cloud frameworks.
• Set up robust scheduling and orchestration with Apache Airflow (Astronomer) or cloud‑native schedulers to achieve >99.5% reliability.
• Design and maintain scalable data models, OLAP/OLTP schemas, data lakes, lakehouses and data meshes.
• Implement Change Data Capture, micro‑batching, delta extracts and partition maintenance.
• Translate business requirements into technical specifications and data‑flow diagrams.
• Present architectural solutions to C‑level executives, highlighting ROI and performance gains.

Required profile

• 5+ years of experience in data management, database design, migration and advanced modeling.
• Proven leadership of data engineering teams (4‑7 members preferred).
• Hands‑on experience with major ETL tools such as Talend, AWS Glue, Azure Data Factory, GCP Dataflow or Apache NiFi.
• Strong expertise in orchestration tools, especially Apache Airflow (Astronomer).
• Production‑grade coding skills in SQL, Python (PySpark, Pandas), Scala, SparkSQL and Bash.
• Extensive knowledge of cloud platforms (AWS, Azure, GCP).

Required skills

• Talend
• AWS Glue
• Azure Data Factory
• GCP Dataflow
• Apache NiFi
• Apache Airflow (Astronomer)
• SQL
• Python (PySpark, Pandas)
• Scala
• SparkSQL
• Bash
• AWS, Azure, GCP cloud services