
Data Engineer/Lead
1 week ago
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).
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