Data Engineering Lead - Python/SQL

Description :

Were looking for a Data Engineer - Lead to shape and scale our data engineering function. In this role, you will lead a high-performing team, define technical strategy, and architect enterprise-scale data platforms.

Youll collaborate with senior leadership, drive cross-functional data initiatives, and ensure excellence in building scalable, secure, and reliable data systems.

This position requires strong leadership, deep technical expertise, and a passion for advancing data capabilities across the organization.

Requirements :

- 7+ years of experience in data engineering, including at least 2+ years in a leadership or lead role.

- Proven ability to lead and manage data engineering teams, provide mentorship, and drive strategic initiatives.

- Strong expertise in architecting enterprise-scale data platforms and multi-tenant infrastructure.

- Hands-on experience with data lake/warehouse solutions (Redshift, BigQuery, Snowflake, Delta Lake, Apache Iceberg).

- Expert-level proficiency in Python, SQL, and data modeling.

- Deep knowledge of distributed systems, data processing frameworks, and system design.

- Advanced experience with cloud platforms (AWS, GCP, Azure), infrastructure as code, and containerization.

- Strong background in real-time and batch data pipelines using Airflow, Kafka, Spark, Flink.

- Experience implementing data governance, lineage, quality frameworks, and observability standards.

- Skilled in performance optimization for queries, storage, and infrastructure at scale.

- Knowledge of CI/CD workflows, testing strategies, and deployment automation.

- Experience with streaming platforms (Kafka, Kinesis) and event-driven architectures.

- Proficiency with modern table formats (Apache Iceberg, Delta Lake) and lakehouse architectures.

- Demonstrated ability in strategic thinking, stakeholder management, and cross-team collaboration.

- Experience in budget planning, vendor management, and technical recruitment.

- Excellent communication and leadership skills to drive collaboration between Data, ML, Analytics, and Engineering teams.

Good to Have :

- Familiarity with data observability tools (e.g., Monte Carlo, Great Expectations).