Job Description :

At Our Client, we are seeking a Data Engineer - Lead to architect and scale enterprise-grade data platforms, manage and mentor a growing team, and drive the design and implementation of high-performance, cloud-native data solutions that power advanced analytics and AI initiatives.

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 lake house 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 :

- Experience with DBT for data transformation and modeling.

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