About the Role:
Work Setup
- Work From Home
- Must be willing to report onsite 1–2 times per month as needed
Experience Required
- Minimum 2 years of experience in Data Quality, Data QA, or Data Analysis
Key Responsibilities
- Perform data quality validation to ensure data accuracy, completeness, consistency, and validity.
- Validate datasets using SQL and identify data issues, discrepancies, and anomalies.
- Develop and execute basic Python scripts for data testing and automation.
- Support validation of structured and unstructured datasets.
- Review and validate ETL/ELT data pipelines and data transformations.
- Work closely with cross-functional teams to resolve data quality issues.
- Ensure data integrity across databases and cloud-based platforms.
- Document findings, recommend improvements, and support continuous data quality initiatives.
Qualifications:
Required
- Minimum 2 years of experience in Data Quality, Data QA, or Data Analysis.
- Strong SQL skills for data validation, querying, and analysis.
- Working knowledge of Python for data testing and automation.
- Solid understanding of data quality principles:
- Accuracy
- Completeness
- Consistency
- Validity
- Experience working with ETL/ELT processes.
- Familiarity with structured and unstructured data.
- Knowledge of cloud platforms such as AWS or Azure.
- Experience working with databases such as MongoDB.
Preferred Qualifications
- Experience with data validation frameworks (e.g., Great Expectations, dbt Tests).
- Familiarity with vector databases and RAG pipeline evaluation.
- Exposure to AI/ML or Large Language Model (LLM) systems.
- Experience evaluating AI-generated outputs.
- Background in healthcare or life sciences data.
- Experience working in an Agile environment.
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
Similar jobs
Show more