Overview

We are looking for a Data Engineer to own the downstream half of our data platform: the MDM pipeline, Snowflake data warehouse, and the data flows that connect them. This role sits at the intersection of master data management and cloud data engineering, responsible for ensuring that clean, goldenized data moves from our MDM platform (Profisee) through a medallion architecture (Bronze/Silver/Gold) into Snowflake, where it powers reporting, analytics, and business applications. You will work alongside an external Profisee specialist to learn and eventually own the MDM platform, while also building and scaling our Snowflake environment. The upstream SQL and ERP data work is handled by a separate team; your focus is on what happens after data enters the MDM pipeline and how it gets to the consumers. This is a hands-on role with high visibility. You will work directly with business stakeholders, IT leadership, and external vendors to deliver the data platform that underpins the One HIPCO vision.

Key Responsibilities

• Snowflake Data Engineering
  • Data Warehouse Build: Design, build, and scale the Snowflake data warehouse to consume golden records from the MDM pipeline. Implement schemas, views, materialized views, and access controls.
  • Medallion Architecture: Build and maintain the Bronze/Silver/Gold data layers (Apache Iceberg format) that sit between the MDM output and Snowflake consumption layer. Ensure data transformation and curation at each layer.
  • Data Pipelines: Build and maintain data pipelines using Snowflake-native features (Snowpipe, Streams, Tasks) and Azure Data Factory to move data through the medallion layers and into Snowflake.
  • Semantic Layer: Work with the analytics team to build a semantic layer on top of Snowflake that supports self-service reporting and consistent metric definitions.
  • App Migration Support: Support the migration of downstream applications (One HIPCO app, Sales Agent app) from direct SQL feeds to the golden Snowflake data path.
• MDM Platform and Data Pipeline
  • MDM Operations: Work alongside the Profisee specialist to learn the MDM platform, data model, and goldenization process. Progressively take ownership of the Profisee environment (Dev, Staging, Production), including configuration, matching rules, pipeline operations, and promotion workflows.
  • Goldenization: Support and eventually own the goldenization process for product, vendor/supplier, and customer data domains, including match/merge/survivorship rule management and AI-assisted matching capabilities.
  • Pipeline Catalogue and Automation: Configure and manage Profisee pipeline catalogue to streamline data processing, automate workflows for data ingestion, validation, enrichment, and approval routing. Evaluate AI-assisted automation opportunities.
  • Cross-Referencing and Dedup: Manage part number cross-referencing across ERPs where different companies use different nomenclatures for the same products. Ensure source system identifiers are maintained throughout the pipeline.
  • Data Quality and Governance: Implement data quality checks, validation rules, and QA gates within the MDM pipeline. Establish and enforce data governance practices across the data flow.
• Ongoing
  • Documentation: Create and maintain technical documentation for the MDM pipeline, Snowflake architecture, data models, goldenization rules, and operational procedures.
  • Integration with SQL Team: Coordinate with the SQL/ERP data team to ensure upstream data feeding into the MDM pipeline meets quality and format requirements.

Required Skills

• 5+ years of experience as a Data Engineer, Cloud Data Engineer, or similar role
• Hands-on experience with Snowflake (database design, Snowpipe, Streams, Tasks, materialized views, clustering keys, query optimization)
• Experience building and maintaining data pipelines using ETL/ELT tools or cloud-native frameworks
• Strong SQL proficiency, including complex queries, stored procedures, and performance tuning
• Experience with medallion architecture (Bronze/Silver/Gold) or similar layered data transformation patterns
• Familiarity with data modeling concepts, dimensional modeling, and data warehouse design
• Experience with Azure services (Data Factory, Azure Data Lake, Azure Functions) or equivalent cloud platform
• Ability to work collaboratively with both technical and non-technical stakeholders
• Strong problem-solving skills with attention to data quality and detail
• Willingness and aptitude to learn new platforms (Profisee MDM) and take ownership with specialist support
• Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field (or equivalent experience).

Preferred Skills

• Experience with Master Data Management (MDM) platforms such as Profisee, Informatica MDM, or similar
• Experience with data integration platforms such as Fivetran, Talend, or Informatica
• Familiarity with Apache Iceberg or Delta Lake formats
• Experience with match/merge/survivorship concepts or data deduplication at scale
• Experience with Azure Data Factory pipeline orchestration
• Experience in distribution, manufacturing, or industrial products industries
• Experience working in a multi-company or multi-ERP environment, particularly post-acquisition integration
• Exposure to data governance frameworks, data cataloging, or data lineage tools
• Experience with Python for data engineering tasks (scripting, API integrations, data transformations)
• Familiarity with Power BI or similar BI tools and semantic layer concepts