Senior DataOps Engineer; Hybrid Data Platforms

My client is hiring a Senior Data Ops Engineer to design, automate, and operate reliable, secure data pipelines across hybrid environments. You'll apply Dev Ops principles to data engineering, ensuring high‑quality datasets power AI, BI, and operational use cases.

• Build & manage CI/CD pipelines for data workloads
• Implement automated testing, schema validation & data contracts
• Enforce metadata, lineage & governance policies
• Monitor pipeline health, performance & cost (dashboards, alerts)
• Support incident response & SLA management
• Collaborate with Data, BI & AI teams to deliver production‑ready data
• Apply RBAC, masking, tokenisation for sensitive data (PII/PHI)
• Maintain lineage, cataloging & quality KPIs
• Optimize performance (partitioning, caching, cost efficiency)

• Databricks
• Spark
• Delta Lake
• ADF
• Airflow
• dbt
• Kafka
• CI/CD (Azure Dev Ops/Git Hub Actions)
• Terraform/Ansible

• 8+ years in engineering, 2+ years in Data Ops/Dev Ops
• Strong experience with data platforms (Databricks, Spark, ADF, dbt)
• Hands‑on CI/CD, IaC & observability
• Solid Linux & distributed systems knowledge
• Experience with CDC (SQL Server/Oracle, Debezium/Golden Gate)
• Understanding of data governance & privacy frameworks

Bachelor's in Computer Science, Engineering, or related field

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