IT Data Analytics Specialist - Data Engineer

Vertiv is hiring an IT Data Analytics Specialist - Data Engineer for an onsite role in Westerville, OH. In this position, you will design and optimize scalable data pipelines using Snowflake and Matillion on AWS, enabling governed, reusable Data Products delivered through a Data Marketplace. You will also help strengthen data reliability through automation, validation, monitoring, and a disciplined approach to quality and governance.

What you’ll build and improve

• Design, build, and maintain scalable ETL/ELT pipelines with Matillion on AWS to ingest, transform, and curate data in Snowflake across raw/staging, silver (cleansed and conformed), and gold (business-ready and aggregated) layers.
• Develop and publish certified Data Products that are governed, documented, reusable, and made available for self-service by analysts, data scientists, and business users.
• Build and optimize Snowflake objects including warehouses, schemas, tables, views, streams, tasks, and stored procedures to support Data Product delivery.
• Improve Snowflake performance using clustering, caching, micro-partitioning, and resource monitoring for reliable and fast Data Product outcomes.
• Support the Data Marketplace by ensuring Data Products are cataloged, discoverable, and compliant with enterprise data governance standards.

Governance, quality, and lifecycle automation

• Define and enforce data contracts, SLAs, and quality standards for each Data Product published to the Marketplace.
• Define and automate data validation, profiling, and quality checks embedded within ETL pipelines to protect Data Product integrity.
• Collaborate with data governance teams on naming standards, lineage tracking, metadata management, and access policies.
• Ensure end-to-end data lineage is traceable from source systems through the bronze/silver/gold layers to the final Data Product.
• Partner with the Data Marketplace product owner to support the Data Product lifecycle (creation, certification, publication, and deprecation).
• Automate Data Product certification workflows, including quality gates and approval processes.

Engineering excellence and collaboration

• Collaborate with data analysts, data scientists, AI/ML teams, product teams, and business stakeholders to translate requirements into clearly defined Data Products.
• Lead code reviews, mentor teammates, and support best practices across the engineering organization.
• Contribute to architecture decisions and participate in strategic data roadmap planning.
• Build CI/CD pipelines for Matillion job deployments and Snowflake object management.
• Create reusable ETL frameworks, templates, and patterns to accelerate new Data Product development.
• Implement monitoring and alerting to drive operational excellence for pipeline and Data Product health.

Required qualifications

• 5+ years of experience as a Data Engineer or similar role.
• Strong expertise with Snowflake (SQL, performance tuning, data modeling, warehouse configuration, streams, tasks).
• Hands-on experience with Matillion on AWS (or comparable ETL/ELT tools such as Talend, Informatica, dbt, Azure Data Factory).
• Solid understanding of Data Product and Data Marketplace concepts, including data contracts and data-as-a-product for self-service consumption.
• Advanced SQL skills, including complex query writing and optimization.
• Strong understanding of data modeling and warehouse/lake concepts, including bronze/silver/gold architecture, dimensional models, and star schemas.
• Experience with AWS.
• Proficiency in Python, Airflow, or other orchestration tools.
• Familiarity with Git and CI/CD and general DevOps practices.
• Knowledge of data governance, metadata management, and data cataloging tools.

Technology stack

• Snowflake, SQL, Matillion, AWS, Talend, Informatica, dbt, Azure Data Factory, Python, Airflow, Git, CI/CD

Preferred qualifications

• Experience building or contributing to an enterprise Data Marketplace or Data Catalog.
• Familiarity with data mesh or data product thinking methodologies.
• Experience with near real-time ingestion tools such as OpenFlow, Kafka, or CDC.
• Exposure to AI/ML data preparation and delivering AI-enabled datasets.
• Experience with data lineage and impact analysis tooling.
• Experience with Oracle Business Applications (ERP/EBS) as source systems is a plus.