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We are expanding our Platform Engineering capability to build, secure, and automate the enterprise Data Platform on cloud and Databricks. In this role, you'll help maintain and improve the underlying infrastructure, ingestion frameworks, CI/CD pipelines, orchestration, and observability that enable Data Engineers and Analytics teams to operate at scale. The ideal candidate has solid platform engineering fundamentals with hands-on DevOps skills across data replication, job scheduling, deployment automation, and cloud operations, and is growing toward independent platform ownership.
Assist with platform upgrades, patching, new flow setup, and environment refresh support.
Support enterprise data replication (HVR) and file-based ingestion patterns from operational systems into the data platform.
Competencies:
Job ID: 153229119
Skills:
monte carlo , Pyspark, Kafka, Data Modeling, Kinesis, Terraform, Python, AWS, Sql, Git, Gcp, Databricks, Azure, Genie AI Functions, Spark Structured Streaming, Databricks Feature Store, Great Expectations, MLflow, Feast, ML pipelines, dimensional design, Databricks Workflows, RAG architectures, Unity Catalog, dbt, Tecton, Delta Lake
Skills:
Docker, Python, Kubernetes, Azure DevOps, LangChain, GitHub Actions, Dataiku, Observability tools, MLflow
Skills:
Spark, Python, Golang, Presto, Trino, Iceberg, Delta Lake
Skills:
Bash Shell Scripting, Databricks, Gitlab, AWS, Python, CI CD, job orchestration platforms, Infrastructure-as-Code, monitoring and observability tools, data replication tools
Skills:
Splunk, Ssh, Autosys, Windows, Grafana, Dynatrace, Ansible, PowerShell, Linux, AWS, Https, Ftps, Python, Bash, Azure, Sftp, Terraform, cd, PGP encryption, Axway B2Bi, IBM Connect Direct, SSL certificates