Manager - Data Quality Engineering
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฎ๐ฏ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฏ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฎ๐ฏ-๐ฏ๐ฌ ๐๐ฃ๐)
Experience: 9+ yrs
Location: Bengaluru, Karnataka, India
Job Type: Full-time
We are looking for an experienced Manager โ Data Quality Engineering to lead data quality initiatives across large-scale data platforms and pipelines. This role combines technical leadership, data quality engineering, test automation, and people management, with a strong focus on ensuring the accuracy, completeness, reliability, and integrity of enterprise data.
You will lead a team of Data Quality Engineers, define automation strategies, and work closely with Data Engineering, Product, Analytics, and other technology teams to validate complex ETL processes, business rules, and data transformations.
Requirements
Key Responsibilities
- Lead and mentor a team of Data Quality Engineers responsible for validating multiple data pipelines and business domains.
- Define and implement automation strategies for complex ETL logic, data transformations, and business rules.
- Drive data validation initiatives across platforms such as Snowflake and Databricks.
- Design, enhance, and maintain scalable data quality and test automation frameworks.
- Partner with Data Engineers, Analysts, Product Managers, and other stakeholders to ensure data accuracy, completeness, and consistency.
- Analyze large-scale datasets to identify data anomalies, quality issues, and business logic discrepancies.
- Establish and improve data quality standards, testing methodologies, and engineering best practices.
- Integrate automated validation into CI/CD pipelines to improve reliability and deployment confidence.
- Work with technologies such as Airflow, Spark, Databricks, and Snowflake to support modern data engineering environments.
- Lead root-cause analysis and resolution of complex data quality and pipeline issues.
- Drive quality engineering practices across Agile teams and contribute to technical planning and delivery.
- Establish processes and metrics to continuously improve data quality and testing effectiveness.
- Manage hiring, performance, career development, and technical growth of team members.
- Foster a culture of engineering excellence, ownership, collaboration, and accountability.
What's Makes You a Great Fit
- 8+ years of professional experience in software testing, data quality engineering, data engineering, or related technical roles.
- At least 2 years of experience in technical leadership or engineering management.
- Proven experience validating complex ETL pipelines, data transformations, and business logic across large-scale systems.
- Strong proficiency in Python and SQL, with experience working with large or terabyte-scale datasets.
- Strong understanding of data quality automation, test frameworks, CI/CD, and validation methodologies.
- Hands-on experience with Snowflake, Databricks, Spark, Airflow, or similar modern data platforms.
- Strong analytical and problem-solving skills with the ability to investigate complex data issues and determine root causes.
- Experience implementing quality engineering practices within Agile development environments.
- Proven ability to hire, mentor, manage, and develop engineering talent.
- Strong communication and stakeholder-management skills, with the ability to collaborate across Engineering, Product, Analytics, and Data teams.
- Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
- A strong ownership mindset and passion for building scalable, reliable, and high-quality data systems.