Data Quality Engineer

Advanced Systems Design is seeking a Data Quality Engineer for our client located in Montgomery, AL.

This position is onsite in Montgomery, AL, and requires in-person availability starting day 1.

A Data Quality Engineer, strong data analyst with deep technical skills in SQL, Purview, Data Pipelines and Data Modeling, plus experience in cloud data environments, automated testing, and collaboration with analytics and engineering teams. Ensures data is not only clean but also ready to support advanced analytics and AI applications.

Data Quality Engineer & Analytics Skills

• Core Technical
  
  Skills:
  
  MUST BE ABLE TO NAVIGATE AN ENVIRONMENT WITH LOW O DATA MATURITY
• Data Profiling & Cleansing:
  Analyze data to identify anomalies, duplicates, outliers, and missing values; apply cleansing techniques to improve data integrity.
• SQL Proficiency:
  Write complex queries to validate data accuracy, perform transformations, and generate reports. (SSIS - ETL LT)
• Python & Other
  
  Languages:
  
  Python is widely used for automation, data validation, and integration with analytics pipelines; SQL is essential for querying and reporting.
• Data Modeling & Warehousing:
  Understand ETL/ELT processes, data warehouse/lake/lakehouse architectures, and data modeling principles.
• Cloud & Modern Data Stack:
  Experience with cloud platforms (AWS, GCP, Azure), modern data warehouses (Snowflake, Big Query), and tools like Spark, Kafka/Kinesis, Hadoop, or S3.
• Data Testing & Observability:
  Design and deploy automated data testing at scale; use observability platforms for real-time monitoring.

Analytics & Data Science Skills

• Data Quality Standards & Metrics:
  Define and enforce data quality benchmarks; measure completeness, accuracy, timeliness, and consistency.
• Root Cause Analysis:
  Identify why data issues occur (ETL bugs, user input errors, system failures) and implement fixes.
• Collaboration with Data Scientists:
  Work with ML/data science teams to ensure training data is clean and reliable.
• Statistical & Trend Analysis:
  Interpret patterns in large datasets to inform quality improvements.

Soft & Communication Skills

• Stakeholder Engagement:
  Gather requirements from business, engineering, and analytics teams; advocate for data quality across the organization.
• Problem-Solving & Attention to Detail:
  Spot and resolve data issues efficiently; maintain high precision in validation.
• Documentation:
  Record quality issues, processes, and improvements for transparency and compliance.

Tools & Platforms

• Query & Analysis: SQL, Python, Spark, Kafka/Kinesis, Hadoop, S3.
• Data Quality Tools:
  Data profiling tools (MS Purview), validation scripts, observability platforms.
• Collaboration:
  
  Jira, Snowflake, or other data governance platforms.

• Knowledge of DAMA-DMBoK, DCAM, MDM concepts, and governance frameworks. (8-10 Years)
• Experience with Microsoft Purview, Fabric, MS Power BI, and Key Vault (5-8 Years)
• Familiarity with AI/ML data readiness and feature-store-aligned data structuring. (5-8 Years)
• Cloud data engineering exposure (Azure, Databricks, GCP). (5-8 Years)

• Bachelor's Degree

• Master's Degree
• DAMA CDMP (Associate/Practitioner)
• EDM Council DCAM
• ASQ Data Quality Credential
• Collibra Data Steward Certification
• Certified Data Steward (eLearning
  
  Curve)
• Cloud/AI certifications (Azure, Databricks, Google)

Advanced Systems Design is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.