Senior Data Platform Engineer: Data Products & Pipelines

Vizient; Irving (TX); On-site; USD 102,000 - 179,000; Full time

Benefits offered by this job

Incentive eligible

Comprehensive benefits

Job summary

Vizient seeks an experienced data engineer to design, build, and scale enterprise data products powering analytics, benchmarking, AI, and decision-support solutions.

You will develop modern data pipelines using Databricks and cloud-native technologies, collaborating with product, analytics, and business teams to transform complex data into trusted, scalable solutions. You will contribute to data modernization and governance initiatives, and mentor engineers.

Qualifications

• Relevant degree preferred.
• 5+ 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 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 with Delta Lake, Unity Catalog, Databricks Asset Bundles, or modern Lakehouse architectures preferred.
• Experience developing data products that support advanced analytics, ML, 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 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 to accelerate delivery across products.
• Lead feature-level technical design, story refinement, and solution development for complex data initiatives.
• Collaborate with architects 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 opportunities to improve platform capabilities and engineering practices.
• Develop technical documentation, engineering standards, procedures, and continuous improvement practices.

Skills

Databricks

Apache Spark

Python

SQL

Data pipelines

Data modeling

CI/CD

Cloud data solutions

Education

Relevant degree preferred

Tools

Azure

AWS

Google Cloud

Delta Lake

Unity Catalog

Databricks Asset Bundles

Job description

Vizient seeks an experienced data engineer to design, build, and scale enterprise data products powering analytics, benchmarking, AI, and decision-support solutions.

You will develop modern data pipelines using Databricks and cloud-native technologies, collaborating with product, analytics, and business teams to transform complex data into trusted, scalable solutions. You will contribute to data modernization and governance initiatives, and mentor engineers.