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Job Description
Structured overview of role & requirementsAbout This Role
Own and manage daily data engineering operations including pipeline monitoring, incident resolution, and workload prioritization within cloud (GCP) and on-premises environments.
Ensure pipeline quality, robustness, SLA compliance, and operational resilience for ingestion workflows and main data assets.
Lead technical delivery of data engineering use cases, mentor junior engineers, and drive continuous improvements in pipeline reliability, observability, and efficiency.
Minimum Requirements
Bachelor’s degree in Computer Science, Engineering, Statistics or related field.
Minimum 10 years of data engineering experience with at least 3 years in lead roles.
6+ years in Big Data technologies including Spark, Hive, Hadoop, Databricks.
Advanced proficiency in Apache Spark (PySpark), Python, SQL (T-SQL, BigQuery), and experience with GCP data stack (BigQuery, Dataflow, Pub/Sub, Cloud Composer).
Ideal Candidate Profile
Experienced leader capable of autonomous delivery and mentoring junior engineers in a hybrid cloud data engineering environment.
Strong technical expertise in designing, optimizing, and managing scalable data pipelines including batch and real-time streaming.
Comfortable managing operational standards, incident escalation, and coordinating across data providers and consumers within a structured data engineering team.