Senior Data Engineer, Data Products & Platforms

You will contribute to data modernization and architecture initiatives, improve engineering standards, and provide technical guidance and mentoring to other engineers. Responsibilities: - Design and build scalable data ingestion, transformation, and delivery pipelines using Databricks, Apache Spark, Python, and SQL. - Develop curated data products that support analytics, benchmarking, reporting, AI, and operational decision-making. - Partner with product, analytics, and business teams to translate complex requirements into reliable and maintainable data solutions. - Modernize analytical assets, prototypes, and notebook-based solutions into governed, production-ready data products. - Implement data quality, observability, lineage, security, and operational monitoring practices. - Contribute to enterprise data architecture, metadata management, and data governance initiatives. - Optimize data pipelines and platforms for performance, reliability, scalability, and cost efficiency. -

Develop reusable data platform capabilities and engineering patterns that accelerate delivery across products and business domains. - Lead feature-level technical design, story refinement, and solution development activities for complex data initiatives. - Collaborate with architects and engineering teams on product-level architecture and technical design decisions. - Troubleshoot complex data, platform, integration, and performance issues and implement sustainable solutions. - Mentor engineers through technical guidance, code reviews, knowledge sharing, and development support. - Evaluate emerging data technologies and recommend opportunities to improve platform capabilities and engineering practices. - Develop technical documentation, engineering standards, operational procedures, and continuous improvement practices. Qualifications: - Relevant degree preferred. - 5 or more years of relevant experience required. - Strong experience with Databricks, Apache Spark, Python, and SQL required. - Experience designing and building production-grade data pipelines, data products, and data platforms required. - Experience developing cloud-based data solutions using Microsoft Azure, AWS, Google Cloud, or comparable cloud technologies required. - Experience implementing CI/CD, automated testing, monitoring, and deployment practices for data solutions required. - Experience with data modeling, distributed processing, performance optimization, and large-scale data engineering preferred. - Experience working with structured and semi-structured data at scale preferred. - Experience diagnosing and resolving complex data, platform, integration, and performance issues preferred. - Experience with Delta Lake, Unity Catalog, Databricks Asset Bundles, or modern Lakehouse architectures preferred. - Experience developing data products that support advanced analytics, machine learning, or AI solutions preferred. - Knowledge of data governance, metadata management, regulatory requirements, and enterprise data ma agement practices preferred. - Experience modernizing legacy analytical solutions and transitioning prototypes into governed production platforms preferred. - Healthcare, financial services, benchmarking, consulting, or analytics industry experience preferred. Estimated Hiring Range: At Vizient, we consider skills, experience, and organizational needs in our compensation approach.