Description

 

Summary

• Data Quality Engineer, strong data analyst with deep technical skills in SQL, Purview, Data Pipelines and Data Modeling
• 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

Core Technical Skills

• MUST BE ABLE TO NAVIGATE AN ENVIRONMENT WITH LOW\NO 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\ELT)
• 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, BigQuery), 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

Required Skills

• Strong experience working in low or immature data environments, establishing data quality processes from scratch (8-10 Years)
• Advanced SQL expertise for complex querying, data validation, and transformation (8-10 Years)
• Hands-on experience with ETL/ELT pipelines (e.g., SSIS or similar tools) (8-10 Years)
• Proficiency in Python for data automation, validation, and pipeline integration (5-8 Years)
• Experience with data profiling and cleansing (anomalies, duplicates, outliers, missing values) (8-10 Years)
• Solid understanding of data modeling and data warehouse/lake/lakehouse architectures (8-10 Years)
• Experience implementing data quality frameworks and metrics (accuracy, completeness, timeliness, consistency) (8-10 Years)
• Experience with cloud data platforms (AWS, Azure, or GCP) and modern data warehouses (e.g., Snowflake, BigQuery) (5-8 Years)

Required Tools & Platforms: (8-10 Years)

• 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

Preferred Skills

• 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)
• Master’s degree preferred

Certifications:

• DAMA CDMP (Associate/Practitioner)
• EDM Council DCAM
• ASQ Data Quality Credential
• Collibra Data Steward Certification
• Certified Data Steward (eLearningCurve)
• Cloud/AI certifications (Azure, Databricks, Google)

Key Skills

Education

Bachelor's degree