Posted:5 days ago|
Platform:
Remote
Full Time
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.
Experience with DBT for data transformation and modeling.
Familiarity with data observability tools (e.g., Monte Carlo, Great Expectations).
GKM IT
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