Title: Data Quality Engineer
Location: Grand Rapids, Michigan
Salary: $120,000 + Bonus & Benefits
Overview
We have partnered with a global retail organisation searching a Data Quality Engineer. This role involves utilizing your expertise and passion to maintain and improve our data quality. You will work closely with our DataOps team, Data Owners, and Data Stewards to establish, implement, and sustain data quality standards and procedures. Furthermore, you will be responsible for identifying and resolving any data quality issues to ensure our data remains accurate, complete, and reliable.
Data Quality Engineer - Responsibilities
- Lead the design, development, and automation of a Data testing framework using Azure and SAP technologies across on-premises and cloud environments.
- Direct API testing and automation for data pipelines, services, warehouses, BI systems, and ML platforms, ensuring unified transactional data validation.
- Utilize programming languages and analytics tools to validate products, ML models, data pipelines, and deliverables, while managing data quality with tools like Collibra.
- Oversee data governance, data profiling, and ETL processes with tools like SAP BODS, SAP SLT, SSIS, and SAP CPI to ensure data quality and accurate metadata documentation.
- Develop automated testing solutions using statistical methods and models, and establish quality metrics to assess data pipelines and products.
- Collaborate with cross-functional teams to implement data science features, apply Agile practices, and support QA with feature and regression testing.
Requirements
- Expert in automated testing for multi-source data ingestion, SQL queries, stored procedures, data warehousing, modeling, and data security (RBAC, RLS, CLS, Data Masking) with programming experience in C#, JavaScript, and Python.
- Proficient across all phases of the delivery lifecycle-from requirements gathering to post-launch support-ensuring efficient and consistent project delivery.
- Skilled in applying and maintaining development standards within the Technical Stack, with the ability to enhance and support existing systems.
- Experienced in quickly diagnosing and resolving complex, cross-platform issues while mentoring others in troubleshooting performance and reliability challenges.
- Strong team player with excellent analytical skills, attention to detail, and adaptability, able to work independently and communicate effectively across the organization.
