Overview: Responsible for expanding and optimizing VNS Health's data architecture and pipeline infrastructure to support cross-functional data needs. This role focuses on enhancing data flow and collection processes, ensuring consistency and scalability across ongoing initiatives. The Data Engineer contributes to the design and implementation of frameworks and processes that support the modernization and re-engineering of data systems, enabling future product development and data-driven initiatives. Collaborates closely with technical and business teams to deliver reliable, high-performance data solutions. Works under general supervision. Responsibilities:
What We Provide
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Referral bonus opportunities
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Generous paid time off (PTO), starting at 30 days of paid time off and 9 company holidays
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Health insurance plan for you and your loved ones, Medical, Dental, Vision, Life and Disability
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Employer-matched retirement saving funds
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Personal and financial wellness programs
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Pre-tax flexible spending accounts (FSAs) for healthcare and dependent care
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Generous tuition reimbursement for qualifying degrees
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Opportunities for professional growth and career advancement
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Internal mobility, generous tuition reimbursement, CEU credits, and advancement opportunities
What You Will Do
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Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
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Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
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Identifies, designs, and implements internal process improvements such as automating manual processes, refactoring legacy code, optimizing data delivery, generating reports, and re-designing infrastructure for greater scalability.
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Performs ongoing data validation required to troubleshoot data related issues and assist in their resolution.
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Provides production support as needed, including during non-business hours and weekends.
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Writes unit/integration tests, contributes to our knowledge base, and documents work.
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Works closely with the data science and business intelligence teams to develop data models, pipelines, reports, and dashboards to support all lines of business.
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Engages non-technical personnel and embraces opportunities to connect technical work to broader business goals.
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Exhibits ability to deliver short-term projects while working on long-term projects.
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Stays abreast of and advocates for best practices in data engineering.
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Participates in special projects and performs other duties as assigned.
Qualifications:
Education:
- Bachelor's Degree in Computer Science, Statistics, Informatics, Information Systems or a related field required
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Master's Degree in Computer Science or a related field preferred
Work Experience:
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Minimum of five years of Python experience required
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Minimum of five years of Shell scripting experience required
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Minimum of five years of object-oriented programming (Java/C++) required
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Minimum of five years working on relational databases and data warehouses required
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Experience with AWS cloud services such as EC2, RDS, S3, Athena, Redshift, and Dynamo required
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Experience with Gitlab/Github CI/CD required
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Experience with data pipeline and workflow management tools such as AWS Glue and Apache Airflow required
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Experience building and optimizing big data pipelines, architectures and data sets required
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Experience with stream-processing systems including PySpark, Storm, and Spark-Streaming required
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Experience with demonstrable Snowflake experience preferred
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Experience with demonstrable Apache Iceberg experience preferred
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Administrative experience (system or database) preferred
Pay Range: USD $98,200.00 - USD $130,800.00 /Yr.
