Data Quality Engineer
Role details
Job location
Tech stack
Job description
We are seeking a highly experienced Data Quality Engineer to join a dynamic team in Montgomery, AL. In this role, you will be responsible for establishing and elevating data quality processes in environments with low or immature data maturity. Your expertise in data profiling, cleansing, and validation will ensure data integrity across complex systems. You will work closely with analytics, engineering, and business stakeholders to design and implement scalable data quality frameworks, automate testing, and optimize data pipelines. This is an excellent opportunity for a data professional passionate about improving data reliability to support advanced analytics and AI initiatives.
Key responsibilities include analyzing large datasets to identify anomalies, cleansing data, developing and maintaining ETL/ELT pipelines, and collaborating on cloud-based data architectures. You will also define and monitor data quality metrics, troubleshoot data issues, and document best practices to enhance data governance.
Ideal candidates will possess deep technical expertise in SQL, Python, data profiling tools like MS Purview, and modern data platforms such as Snowflake and AWS. Experience in establishing data quality standards, working within cloud environments, and collaborating with data science teams is essential.
Requirements
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8-10 years of experience working in low or immature data environments, establishing data quality processes from scratch
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Advanced SQL skills for complex queries, data validation, and transformations (8-10 years)
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Hands-on experience with ETL/ELT pipelines (e.g., SSIS or similar tools) (8-10 years)
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Proficiency in Python for automation, validation, and pipeline integration (5-8 years)
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Expertise in data profiling, cleansing, and anomaly detection (8-10 years)
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Strong understanding of data modeling, data warehouses, lakes, and lakehouses (8-10 years)
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Experience with cloud platforms (AWS, Azure, GCP) and modern data warehouses like Snowflake or BigQuery (5-8 years)
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Proficiency with data analysis and quality tools such as MS Purview, observability platforms, and data governance tools (8-10 years)
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Educational background with a Bachelor's Degree; Master's degree preferred
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Certifications such as DAMA CDMP, EDM Council DCAM, Collibra Data Steward, or cloud/AI certifications (preferred)
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Knowledge of data governance frameworks, MDM concepts, and AI/ML data readiness (5-8 years)
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Experience with Microsoft Purview, Fabric, Power BI, and cloud data engineering (5-8 years)