Data QA/QC Engineer

5 days ago

Noida, Uttar Pradesh, India RMSI Cropalytics Full time ₹ 9,00,000 - ₹ 12,00,000 per year

About the Role

We are seeking detail-oriented Data QA/QC Engineer who will work closely with the database and analytics team members to ensure the quality, accuracy, and consistency of organizational data. The role involves performing QA/QC checks on data pipelines, validating data in PostgreSQL databases, and supporting day-to-day data operations using Excel and SQL. The ideal candidate has strong analytical skills, attention to detail, and experience in managing large datasets.

Key Responsibilities:

  • Perform QA/QC checks on incoming and processed datasets to ensure accuracy, completeness, and consistency.
  • Perform data cleaning, transformation, and validation in Excel and PostgreSQL.
  • Collaborate with database engineers and analysts to validate data quality across PostgreSQL databases.
  • Write and execute SQL queries to audit, validate, and reconcile data.
  • Identify data anomalies, errors, and gaps; work with the team to resolve them.
  • Document QA/QC procedures, test cases, and maintain audit logs of checks performed.
  • Support automation of data validation processes where possible.
  • Ensure compliance with data governance, security, and quality standards.

Required Skills & Qualifications:

  • Bachelors degree in Computer Science, Information Technology, Statistics, or related field.
  • 2–4 years of experience in data quality assurance, data validation, or database testing.
  • Strong hands-on experience with PostgreSQL (writing queries, joins, aggregations, validations).
  • Proficiency in Excel (advanced formulas, pivot tables, data cleaning).
  • Strong analytical and problem-solving skills with attention to detail.
  • Good documentation skills for QA/QC processes.
  • Work closely with database team members.

Preferred Skills:

  • Experience with other databases (MySQL, SQL Server, Oracle).
  • Exposure to data warehousing and ETL pipelines.
  • Familiarity with Python or R for data validation and automation.
  • Experience in QA/QC for large-scale datasets and agri/environmental datasets.

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