Data ML Engineer

Job ID : 83962-1Job Title: Data ML EngineerLocation : Bellevue, WA - OnsiteDuration : 6 months + possible extensionRate Range: $50 - $54/hour on W2 (All inclusive)Note: Applicants must be willing to work on W2 only.Role SummaryWe are seeking a skilled Data Machine Learning Engineer with strong experience in Python| PySpark| and Azure Synapse Analytics| along with working knowledge of Azure Machine Learning Studio| Azure Data Explorer (Kusto)| and Azure Storage services. The role involves building scalable data pipelines| enabling ML workflows| and supporting analytics at enterprise scale.Key ResponsibilitiesDesign| develop| and maintain data processing pipelines using PySpark on Azure Synapse.Build and operationalize machine learning workflows using Azure ML Studio| including data preparation| training| and inference support.Develop robust Python-based data processing and analytics solutions.Ingest| transform| and analyze large-scale datasets from Azure Storage (Blob ADLS Gen2).Query and analyze telemetry and operational data using Azure Data Explorer (Kusto) for insights and troubleshooting.Collaborate with data scientists| platform engineers| and product teams to enable endtoend data and ML solutions.Ensure data quality| reliability| performance| and cost efficiency across pipelines.Support production deployments| monitoring| and troubleshooting of data and ML workloads.Required SkillsStrong proficiency in Python for data processing and automation.Hands-on experience with PySpark and distributed data processing.Experience working with Azure Synapse Analytics (Spark pools).Familiarity with Azure Machine Learning Studio concepts and workflows.Experience with Azure Storage services (Blob Storage ADLS Gen2).Basic to intermediate knowledge of Azure Data Explorer (Kusto) and KQL.Understanding of data engineering best practices (partitioning| performance tuning| fault tolerance).Essential SkillsPythonPySparkAzure Synapse AnalyticsAzure Machine Learning StudioAzure Data Explorer (Kusto)Azure Storage ServicesData EngineeringMachine Learning WorkflowsCompany Benefits & CultureInclusive and diverse work environmentOpportunities for professional growth and developmentComprehensive health and wellness benefits