We are looking for a skilled Data Quality Engineer to join our driven team, collaborating on data ingestion processes and enabling the effective utilization of high-quality data across the company. In this role, you will contribute to an innovative supply-chain data analytics platform that leverages artificial intelligence to transform supply-chain insights and deliver domain-specific recommendations.

 

Responsibilities

• Define, implement, and maintain tooling and processes for data quality management from scratch
• Build and enforce data quality validations within ETL pipelines
• Set up monitoring dashboards and alerts to ensure continuous data quality tracking
• Collaborate with cross-functional teams to ingest, profile, and standardize data from multiple external sources
• Leverage SQL and Python to analyze and enhance data quality metrics
• Utilize AWS services, such as reading from S3, for data profiling and validation tasks
• Partner with clients to identify and resolve data quality issues, ensuring effective communication and delivery of solutions
• Work effectively amidst ambiguity and in a fast-paced startup environment to execute tasks independently
• Foster transparency and proactivity within the team and with stakeholders

 

Requirements

• Strong experience spanning over 2 years as a Data Quality Engineer or in similar roles, with a proven ability to establish processes and tools
• Showcase of implementing data quality checks in ETL pipelines and creating interactive dashboards and alerts
• Proficiency in SQL and Python for data quality tasks
• Familiarity with AWS services, with a focus on data profiling and reading data from S3
• Background in client-facing roles, demonstrating excellent communication skills and proactivity
• Capability to independently execute tasks and maintain productivity without constant direction
• Flexibility to adapt to a fast-paced startup environment with transparent and collaborative workflows
• English level B1+ for effective communication

 

Nice to have

• Expertise in profiling data using Glue Data Quality
• Hands-on experience working with Databricks and PySpark
• Familiarity with multiple data quality monitoring frameworks or tools such as Great Expectations, SODA, Lightup, etc.

 

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn