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IT Data Analytics Specialist - Data Engineer

Vertiv
Westerville, USA
Mid · 5+ years experience
Onsite
Discovered 2 weeks ago
SQLAWSAzureOraclePython

Full Job Posting

Key Responsibilities

  • Data Products Engineering & ETL Development
  • Design, build, and maintain scalable ETL/ELT pipelines using Matillion on AWS to ingest, transform, and curate data across incoming (raw/staging), silver (cleansed & conformed), and gold (business-ready/aggregated) layers in Snowflake.
  • Develop and publish certified Data Products — governed, documented, and reusable datasets made available through the Data Marketplace for self-service consumption by analysts, data scientists, and business users.
  • Develop and optimize Snowflake objects including warehouses, schemas, tables, views, streams, tasks, and stored procedures to support Data Product pipelines.
  • Optimize Snowflake performance through clustering, caching, micro-partitioning, and resource monitoring to ensure Data Products are delivered with reliability and speed.
  • Data Marketplace & Data Governance
  • Support the design and population of the Data Marketplace, ensuring Data Products are cataloged, discoverable, and compliant with enterprise data governance standards.
  • 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 guarantee Data Product integrity.
  • Collaborate with data governance teams to implement naming standards, lineage tracking, metadata management, and access policies for Data Products.
  • Ensure data lineage is traceable end-to-end from source systems through bronze/silver/gold layers to the final Data Product.
  • Collaboration & Delivery
  • Work closely with data analysts, data scientists, AI/ML teams, product teams, and business stakeholders to understand requirements and translate them into well-defined Data Products.
  • Partner with the Data Marketplace product owner to define the Data Product lifecycle (creation, certification, publication, deprecation).
  • Lead code reviews, provide mentorship, and support best practices across the engineering team.
  • Contribute to architectural decisions and participate in strategic data roadmap planning.
  • Automation & DevOps
  • Build CI/CD pipelines for Matillion job deployments and Snowflake object management.
  • Develop reusable ETL frameworks, templates, and patterns to accelerate the creation of new Data Products.
  • Implement monitoring, alerting, and operational excellence practices for data pipelines and Data Product health.
  • Automate Data Product certification workflows, including quality gates and approval processes.

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 (data contracts, data-as-a-product, self-service data consumption).
  • Advanced SQL skills; ability to write complex queries and optimize them.
  • Strong understanding of data modeling, dimensional models, star schemas, and data warehouse/data lake concepts (bronze/silver/gold architecture).
  • Experience with cloud platforms, specifically AWS.
  • Experience with Oracle Business Applications (ERP/EBS) as source systems is a plus.
  • Proficiency in Python, Airflow, or other orchestration tools.
  • Familiarity with Git, CI/CD, and general DevOps practices.
  • Knowledge of data governance principles, metadata management, and data cataloging tools.

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 data ingestion tools (e.g., OpenFlow, Kafka, 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.

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