Senior Data Engineer, Data Products & Platforms

Vizient•Chicago, IL

1d•$102,400 - $179,000

About The Position

In this role, you will design, build, and scale enterprise data products that power analytics, benchmarking, AI, and decision-support solutions. You will develop modern data pipelines, curated data assets, and reusable platform capabilities using Databricks and cloud-native technologies while partnering with product, analytics, and business teams to transform complex data into trusted, scalable solutions. You will contribute to data modernization and architecture initiatives, improve engineering standards, and provide technical guidance and mentoring to other engineers.

Requirements

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.

Nice To Haves

Relevant degree preferred.
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 management 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.

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.