Data Quality Engineer

Key Responsibilities

• Quality Assurance & Quality Checking: Implement and maintain data quality to ensure the accuracy and reliability of data throughout the ETL process.
• ETL Processes: Design, develop, and optimize ETL workflows to efficiently transfer data from file transfer services to S3 buckets and Snowflake.
• Data Integration: Ensure seamless data integration into data platform, enabling efficient consumption by downstream applications and reporting tools.
• Data Quality Management: Address data quality challenges, including inconsistencies in source data that do not meet ingestion requirements, which can lead to load failures or data backouts.
• Collaboration: Work closely with business owners, data analysts, business intelligence teams, and other stakeholders to understand data requirements and deliver high-quality data solutions.
• Monitoring & Troubleshooting: To preserve data flow and integrity, monitor pipelines, identify issues, and implement solutions.
• Demonstrated mid-level+ experience in data engineering, with an emphasis on data quality assurance and ETL processes.
• Expertise in Python, PyPI, and SQL.