We are seeking a highly skilled Data Product's Engineer with deep expertise in Snowflake and strong hands-on experience with Matillion on AWS. The ideal candidate will design, build, and optimize scalable data pipelines that feed our Data Marketplace and enable the creation, publication, and consumption of certified Data Products across the enterprise.
This role is central to our Data Marketplace strategy — ensuring data flows reliably from source systems through our silver, and gold layers, and is curated, governed, and made discoverable as reusable Data Products. The ideal candidate thrives in complex, enterprise-level environments, collaborates effectively with cross-functional teams, and is passionate about delivering high-quality, governed, and AI-enabled data assets.
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.