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# Data Quality Analyst

- **Company:** Bridgetown Consulting Group
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $104,000.0 - $114,400.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, Data Validation, Data Cleansing, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Profiling, Data Warehousing, Relational Databases, Database Testing, Python (Programming Language), Metadata, Microsoft SQL Server, Operational Databases, SQL Databases, Enterprise Data Management, Freeform SQL, Snowflake, Pyspark, Information Technology, Playwright, Data Analytics, Data Management, Azure Synapse Analytics, Data Pipelines, Databricks
- **Published:** August 27, 2026
- **Apply:** https://www.dice.com/job-detail/c8b9aec1-ddcb-4208-b76a-dcfab3454b8f

## About the Role

* 5+ years of experience in Data Quality, Data Analysis, Data Testing, or ETL Testing.
 * Strong hands-on SQL and experience with relational databases and data warehouses.
 * Experience with data profiling, cleansing, validation, reconciliation, and ETL/ELT testing.
 * Experience in Playwright
 * Experience with platforms such as Snowflake, Databricks, Azure Synapse, SQL Server, or similar.
 * Knowledge of Python/PySpark and data quality tools is an advantage.
 * Strong analytical, problem-solving, communication, and stakeholder-management skills., Bachelor s degree in Computer Science, IT, Engineering, Data Analytics, or a related field, or equivalent experience.

## Description

We are looking for a Data Quality Analyst with strong experience in SQL, data validation, ETL/ELT testing, data profiling, and reconciliation. The role will ensure enterprise data is accurate, complete, consistent, and reliable across data platforms and downstream applications., * Perform data profiling, validation, reconciliation, and quality checks across large datasets.

 * Write advanced SQL queries to identify anomalies, duplicates, missing data, and transformation issues.
 * Validate ETL/ELT pipelines and perform source-to-target testing and reconciliation.
 * Define and implement data quality rules, metrics, controls, and automated checks.
 * Perform root-cause analysis and work with Data Engineering and business teams to resolve data issues.
 * Monitor data quality KPIs and support dashboards, analytics, reporting, and production data issues.
 * Support data governance, lineage, metadata, and data quality standards.


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