Lead Data Platform Engineer

Job summary

Lead Data Platform Engineer to design, build, and optimize scalable data platforms and pipelines for enterprise analytics, combining hands-on engineering with technical leadership.

Qualifications

• 8+ years of experience in data engineering, including 2+ years in a technical leadership role.
• Strong Python skills (Pandas, NumPy, PySpark) and experience with Impala.
• Hands-on experience with Hadoop, Databricks, and large-scale data processing.
• Advanced SQL and experience with relational and distributed databases.
• Experience with cloud platforms such as Azure or AWS, including Databricks or Snowflake.
• Strong knowledge of ETL/ELT tools such as Apache Airflow, Apache NiFi, or Azure Data Factory.
• Experience with CI/CD, DevOps practices, and enterprise data platforms.
• Understanding of data modeling, governance, and performance optimization.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and optimize data platforms using Hadoop, Databricks, and cloud-based technologies.
• Integrate structured and semi-structured data into reliable, high-quality data solutions.
• Partner with cross-functional teams to translate business and analytics requirements into scalable engineering solutions.
• Lead technical design discussions and promote best practices in data modeling, performance optimization, and governance.
• Mentor data engineers and contribute to engineering standards, architecture, and platform scalability.
• Support innovation through proof-of-concepts, automation, and continuous platform improvements.

Skills

Relocation