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Sr. Azure Data & ML Engineer – Databricks, Python & MLOps

Design, develop, and maintain scalable data ingestion, transformation, and ETL/ELT pipelines; build and optimize Azure-based data platforms; support deployment and operationalization of machine learning models; implement monitoring, logging, troubleshooting, and performance optimization; collaborate with data scientists and engineering teams; develop reusable, automated components following cloud engineering best practices.

  • Mason, Ohio, United States
  • Full-time
  • Hybrid
  • Posted Nov 13, 2026
INDUSTRYSoftware & InternetSaaS & Enterprise Software

Responsibilities

  • Design, develop, and maintain scalable data ingestion, transformation, and ETL/ELT pipelines.
  • Build and optimize Azure-based data platforms using Databricks, Data Lake, Synapse, and related technologies.
  • Support deployment and operationalization of machine learning models through CI/CD and MLOps practices.
  • Implement monitoring, logging, troubleshooting, and performance optimization for data and ML workloads.
  • Collaborate with data scientists and engineering teams to translate requirements into production-ready solutions.
  • Develop reusable, automated components following cloud engineering best practices.

Skills

Microsoft Azure data engineering servicesPythonSQLScalaSparkDatabricksCI/CD pipelinesDevOpsMLOps practicesAzure Data FactorySynapse AnalyticsAzure Data LakeMLflowDockerKubernetesAKSDelta LakeParquetinfrastructure as codeorchestration toolscloud monitoringenterprise data integrationsSAP CDCAgile developmentAzureDatabricksData LakeSynapseMLflowDockerKubernetesAKSDelta LakeParquet

Benefits

  • Health Benefits
  • Referral Program
  • Excellent growth and advancement opportunities

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Full description

Our Client, an IT Services and Consultant company, is looking for a Sr. Azure Data & ML Engineer – Databricks, Python & MLOpsr for their Mason, OH/ Hybrid location. Responsibilities: Design, develop, and maintain scalable data ingestion, transformation, and ETL/ELT pipelines. Build and optimize Azure-based data platforms using Databricks, Data Lake, Synapse, and related technologies. Support deployment and operationalization of machine learning models through CI/CD and MLOps practices. Implement monitoring, logging, troubleshooting, and performance optimization for data and ML workloads. Collaborate with data scientists and engineering teams to translate requirements into production-ready solutions. Develop reusable, automated components following cloud engineering best practices. Requirements: Proven hands-on experience as a Data Engineer, ML Engineer, or Cloud Platform Engineer. Strong experience with Microsoft Azure data engineering services. Proficiency in Python, SQL, and/or Scala. Experience developing and supporting production-grade data pipelines. Experience with Spark, Databricks, or comparable big data processing frameworks. Familiarity with CI/CD pipelines, DevOps, and MLOps practices. Ability to independently design, develop, troubleshoot, and deliver technical solutions. Strong communication skills and experience working with cross-functional teams. Preferred Qualifications Experience with Azure Data Factory, Synapse Analytics, and Azure Data Lake. Experience with MLflow, Docker, Kubernetes/AKS, and containerized workloads. Knowledge of Delta Lake, Parquet, and other common data formats. Experience with infrastructure as code, orchestration tools, and cloud monitoring. Exposure to enterprise data integrations, including SAP CDC. Experience working in Agile development environments Years of Experience: 13.00 Years of Experience Why Should You Apply? Health Benefits Referral Program Excellent growth and advancement opportunities

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