Senior Healthcare Data Systems Analyst

VLink, Inc.

Chicago (IL)

Hybrid

USD 76,000 - 90,000

Full time

3 days ago

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Job summary

VLink, Inc. seeks a Senior Business Systems Analyst specialized in healthcare payor data to analyze, design, and support enterprise data platforms. You will work across Databricks, Spark, Python, SQL, and ADF to build scalable pipelines and data processing solutions.

You will collaborate with stakeholders and engineers in an Agile environment, focusing on data governance, quality, and lineage while ensuring compliance with healthcare payor requirements across multiple sites.

Qualifications

10+ years of experience in systems analysis, data engineering, and enterprise data integration.
U.S. healthcare payor, Medicare/Medicaid experience, including claims, member enrollment, eligibility, provider, and healthcare data management.
Strong hands on experience with Python, PySpark, Apache Spark, SQL, Databricks, and Azure Data Factory (ADF).
Experience analyzing, designing, developing, and supporting enterprise scale data processing applications and ETL/ELT pipelines.
Strong experience gathering business and technical requirements, performing system impact analysis, documenting functional specifications, and developing source to target data mappings.
Hands on experience with Azure Data Factory (ADF) for data ingestion, transformation, integration, and workflow orchestration.
Experience with Hadoop ecosystem technologies, including Hadoop/HDFS and Hive.
Strong SQL skills, including complex queries, stored procedures, data transformations, reconciliation, and performance optimization.
Experience developing, analyzing, and supporting ETL workflows using SSIS.
Experience with Unix/Linux Shell Scripting and enterprise job scheduling tools such as Control M.
Strong understanding of Delta Lake, Databricks Workflows, Lakehouse architecture, data warehousing, data modeling, and enterprise data integration.
Experience with data profiling, data validation, source to target reconciliation, data quality, troubleshooting, and root cause analysis.
Experience preparing business requirements, functional specifications, technical documentation, data flow diagrams, and system integration specifications.
Experience supporting application development, integration testing, UAT, production deployments, and incident resolution.
Experience working in Agile/Scrum environments with strong analytical, problem solving, stakeholder communication, and cross functional collaboration skills.
Experience with Azure cloud services, including ADLS Gen2, Azure Synapse Analytics, and Azure DevOps.
Experience with AWS services, including S3, Glue, EMR, Lambda, and Redshift.
Knowledge of Kafka, Airflow, Java/Scala, Git, Jenkins, and CI/CD pipelines.
Experience with Power BI, SSRS, Tableau, or other enterprise reporting and analytics tools.
Experience with data governance, metadata management, data lineage, data quality frameworks, and enterprise data management practices.
Prior experience supporting large scale enterprise data platforms in healthcare, insurance, or other regulated industries.

Responsibilities

Analyze, design, develop, and support enterprise data management solutions, Big Data platforms, ETL/ELT pipelines, and data integration processes.
Collaborate with business stakeholders, data architects, and engineering teams to gather, analyze, and translate business requirements into functional and technical specifications.
Perform system analysis, impact assessments, gap analysis, data mapping, and source to target transformation analysis across enterprise data platforms.
Design, develop, and enhance large scale data processing solutions using Databricks, Apache Spark, PySpark, Python, Hadoop/HDFS, Hive, and Azure Data Factory (ADF).
Analyze and support Databricks notebooks, Spark jobs, Delta Lake tables, and Lakehouse data processing workflows.
Design and maintain data ingestion, transformation, and integration pipelines using Azure Data Factory (ADF), including activities, triggers, parameters, and dependencies.
Develop and optimize complex SQL queries, stored procedures, data transformations, and source to target mapping specifications.
Analyze, develop, and maintain ETL workflows using SSIS and modern cloud based data integration technologies.
Develop and maintain reusable Python, PySpark, and Unix/Linux Shell Scripts for data processing, automation, validation, and operational support.
Analyze data integration requirements across relational databases, APIs, files, cloud storage, and enterprise applications.
Support batch processing, job scheduling, dependency management, and workflow orchestration using Control M, ADF, and Databricks Workflows.
Perform data profiling, validation, reconciliation, root cause analysis, and troubleshooting to ensure data accuracy, completeness, and integrity.
Analyze and optimize Spark jobs, Databricks workloads, SQL queries, and data pipelines for performance, scalability, and reliability.
Prepare functional specifications, technical design documents, data mapping documents, process flows, and system integration documentation.
Collaborate with developers, QA teams, Product Owners, Scrum Masters, and architects to support solution development, system testing, integration testing, and release activities.
Participate in Agile/Scrum ceremonies, including sprint planning, backlog refinement, daily stand ups, reviews, and retrospectives.
Support production deployments, incident investigation, defect resolution, change management, and post deployment validation to maintain enterprise data platform stability.