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Big Data Engineer - Medicare/Medicaid

Remote, USA Full-time Posted 2025-07-27

Job Summary

We are seeking a highly skilled and forward-thinking Big Data Engineer to join our healthcare data team. This role encompasses the end-to-end design, development, and management of large-scale data systems tailored for healthcare analytics. The ideal candidate will be responsible for architecting and maintaining robust, scalable, and secure data pipelines that support critical decision-making across the organization. This position requires deep technical expertise in modern Big Data tools, real-time and batch data integration, and a strong understanding of data governance and compliance in healthcare environments.

    Knowledge/Skills/Abilities
  • Architect and implement scalable, high-performance Big Data solutions that support structured and unstructured data from diverse sources.
  • Build and manage batch and real-time data ingestion/extraction pipelines using tools like Kafka, Spark Streaming, and Talend.
  • Develop reusable and efficient ETL frameworks using Python/Scala for high-volume data transformation and movement.
  • Design and optimize data models to support analytical and operational use cases, including healthcare claims and utilization data.
  • Collaborate with cross-functional teams, including data scientists, analysts, and business partners, to translate requirements into robust data products.
  • Deploy, monitor, and troubleshoot Hadoop-based infrastructure using tools such as Cloudera Manager, Ambari, and Zookeeper.
  • Enforce data quality, security, and compliance standards using tools such as Kerberos, Ranger, and Sentry.
  • Implement web services and APIs (REST/SOAP) to enable seamless integration with applications and visualization platforms.
  • Contribute to data governance initiatives, including metadata management, lineage tracking, and quality assurance.

Job Qualifications

    Required Qualifications
  • Minimum 3 years of hands-on experience in Big Data engineering, data integration, and pipeline development.
  • Proficiency in Python, Java, or Scala for data transformation and system scripting.
  • Expertise in Big Data tools: Spark, Hive, Impala, Presto, Phoenix, Kylin, and Hadoop (HDFS, YARN).
  • Experience building real-time stream-processing systems using Kafka, Storm, or Spark Streaming.
  • Strong knowledge of NoSQL databases like HBase and MemSQL, and traditional RDBMS including PostgreSQL, Oracle, and SQL Server.
  • Skilled in ETL design and development using tools such as Talend or Informatica.
  • Demonstrated experience in deploying and monitoring big data infrastructure with Ambari, Cloudera Manager, and Zookeeper.
  • Solid understanding of data warehousing, data validation, data quality checks, metadata management, and governance.
    Preferred Qualifications
  • 5+ years of progressive experience in Big Data engineering or analytics.
  • Prior experience working in the healthcare industry with familiarity in clinical, claims, or care management data.
  • Experience with cloud platforms (AWS, Azure) and containerization tools (Docker, Kubernetes).
    Technical Environment
  • Big Data Ecosystem: Hadoop, Spark, Hive, Kafka, Presto, Impala, Phoenix, Kylin, Zookeeper
  • Streaming & Messaging: Kafka, Spark Streaming, Storm
  • ETL & Integration: Talend, Informatica, Python/Scala-based ETL
  • Programming Languages: Python, Java, Scala, SQL
  • Databases: HBase, MemSQL, PostgreSQL, Oracle, SQL Server
  • Cloud & DevOps: AWS, Azure, Docker, Kubernetes, Git
  • Security & Governance: Kerberos, Ranger, Sentry, Metadata Management
  • Monitoring Tools: Ambari, Cloudera Manager
  • APIs: REST, SOAP

To all current Molina employees: If you are interested in applying for this position, please apply through the intranet job listing.

Molina Healthcare offers a competitive benefits and compensation package. Molina Healthcare is an Equal Opportunity Employer (EOE) M/F/D/V.

    Pay Range: $77,969 - $171,058 / ANNUAL
  • Actual compensation may vary from posting based on geographic location, work experience, education and/or skill level.

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