Data Quality Engineer

3 weeks ago

Pune, India SUPERSOURCING TECHNOLOGIES PRIVATE LIMITED Full time

Job Summary :

We are seeking a highly motivated and detail-oriented Data Quality Engineer to join our growing team. You'll work closely with Data Engineers, Data scientists, and business team to ensure the accuracy, completeness, and reliability of our data through rigorous testing of ETL workflows, data pipelines and building robust data quality checks. You will play a critical role in maintaining data integrity and supporting data-driven decision-making across the organization.

Key Responsibilities :

- Analyze business and technical requirements to design, develop, and execute comprehensive test plans for ETL pipelines and data transformations.

- Perform data validation, reconciliation, and integrity checks across various data sources and target systems.

- Build and automate data quality checks using SQL and/or Python scripting.

- Identify, document, and track data quality issues, anomalies, and defects.

- Collaborate with data engineers, developers, QA, and business stakeholders to understand data requirements and ensure data quality standards are met.

- Define data quality KPIs and implement continuous monitoring frameworks.

- Participate in data model reviews and provide input on data quality considerations.

- Perform root cause analysis for data discrepancies and work with teams to drive resolution.

- Ensure alignment to data governance policies, standards, and best practices.

Qualifications Required :

- Bachelor's degree in Computer Science, Information Technology, or a related field.

- 4 to 7 years of experience as a Data Quality Engineer, ETL Tester, or a similar role.

- Strong understanding of ETL concepts, data warehousing principles, and relational database design.

- Proficiency in SQL for complex querying, data profiling, and validation tasks.

- Familiarity with data quality tools and testing methodologies.

- Excellent analytical and problem-solving skills with a strong attention to detail.

- Ability to work independently and collaboratively in a fast-paced environment.

Preferred :

- Experience with data quality frameworks (e.g., Soda, Great Expectations, Deequ, Monte Carlo, DBT Test).

- Experience with modern cloud data ecosystems (AWS, Snowflake, Apache Spark, Redshift).

- Advanced knowledge of SQL, including the ability to write stored procedures, triggers, analytic/windowing functions, and performance tuning.

- Familiarity with data pipeline tools like Airflow, DBT, or Informatica.

- Experience integrating data validation processes into CI/CD pipelines using tools like GitHub Actions, Jenkins, or similar.

- Background to big data platforms, data lakes, or non-relational databases.

- Understanding of data lineage, and master data management (MDM) concepts.

- Experience with Agile/Scrum development methodologies.

(ref:hirist.tech)

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