Need only Locals to CA, Lead Data Engineer with Healthcare Experience , Ontario, CA, Hybrid
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David
Oct 6, 2026, 11:18:56 AM (3 days ago) Oct 6
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Job Title: - Lead Data Engineer with Healthcare Experience
Location: Ontario, CA, Hybrid
Need Local | No relocation |
Experience:- 12+
Over View
• We are looking for an experienced Lead Data Platform Engineer to drive the design, build, and optimization of our enterprise data platform.
• This role will lead technical strategy, guide engineering best practices, and work closely with cross-functional teams to deliver scalable, secure, and high-performing data solutions across Hadoop, Hive, and Azure—including Databricks.
Key Responsibilities
• Lead the architecture, development, and enhancement of large-scale data platforms supporting analytics, machine learning, and operational workloads.
• Design and optimize big data solutions leveraging Hadoop ecosystem technologies such as HDFS, Hive, Spark, YARN, and related components.
• Develop and manage data pipelines and transformations using Azure Data services (Data Lake Storage, Data Factory, Synapse, Databricks).
• Implement and enforce robust data governance, security, and quality frameworks across all data layers.
• Partner with data engineering, analytics, product, and infrastructure teams to translate business needs into scalable technical designs.
• Drive performance tuning, capacity planning, and cost optimization across both on-premise and cloud data platforms.
• Mentor and technically guide data engineers; establish engineering standards, reusable patterns, and best practices.
• Oversee CI/CD practices, deployment, and monitoring for data workflows.
• Evaluate emerging technologies and contribute to long-term platform strategy and modernization initiatives.
Required Qualifications
• 12+ years of experience in data engineering or data platform roles, with 3+ years in a technical lead or architect capacity.
• Strong hands-on experience with Hadoop ecosystem components (HDFS, Hive, Spark, Oozie, Ranger, Airflow etc.).
• Deep expertise with Azure data services (Azure Data Lake Storage, Azure Data Factory, Azure Synapse, Azure Functions, Key Vault).
• Advanced experience building solutions in Databricks, including Spark optimization, Delta Lake, and Unity Catalog.
• Proficiency in Python, SQL, and distributed data processing frameworks.
• Experience with DevOps practices, CI/CD pipelines, and Infrastructure-as-Code (e.g., Terraform or ARM).
• Strong understanding of data modeling, storage formats (Parquet, ORC, Delta), and data governance frameworks.
• Proven ability to lead technical teams, communicate clearly, and influence architecture decisions
Location: Ontario, CA, Hybrid
Need Local | No relocation |
Experience:- 12+
Over View
• We are looking for an experienced Lead Data Platform Engineer to drive the design, build, and optimization of our enterprise data platform.
• This role will lead technical strategy, guide engineering best practices, and work closely with cross-functional teams to deliver scalable, secure, and high-performing data solutions across Hadoop, Hive, and Azure—including Databricks.
Key Responsibilities
• Lead the architecture, development, and enhancement of large-scale data platforms supporting analytics, machine learning, and operational workloads.
• Design and optimize big data solutions leveraging Hadoop ecosystem technologies such as HDFS, Hive, Spark, YARN, and related components.
• Develop and manage data pipelines and transformations using Azure Data services (Data Lake Storage, Data Factory, Synapse, Databricks).
• Implement and enforce robust data governance, security, and quality frameworks across all data layers.
• Partner with data engineering, analytics, product, and infrastructure teams to translate business needs into scalable technical designs.
• Drive performance tuning, capacity planning, and cost optimization across both on-premise and cloud data platforms.
• Mentor and technically guide data engineers; establish engineering standards, reusable patterns, and best practices.
• Oversee CI/CD practices, deployment, and monitoring for data workflows.
• Evaluate emerging technologies and contribute to long-term platform strategy and modernization initiatives.
Required Qualifications
• 12+ years of experience in data engineering or data platform roles, with 3+ years in a technical lead or architect capacity.
• Strong hands-on experience with Hadoop ecosystem components (HDFS, Hive, Spark, Oozie, Ranger, Airflow etc.).
• Deep expertise with Azure data services (Azure Data Lake Storage, Azure Data Factory, Azure Synapse, Azure Functions, Key Vault).
• Advanced experience building solutions in Databricks, including Spark optimization, Delta Lake, and Unity Catalog.
• Proficiency in Python, SQL, and distributed data processing frameworks.
• Experience with DevOps practices, CI/CD pipelines, and Infrastructure-as-Code (e.g., Terraform or ARM).
• Strong understanding of data modeling, storage formats (Parquet, ORC, Delta), and data governance frameworks.
• Proven ability to lead technical teams, communicate clearly, and influence architecture decisions
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