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Algoleap Technologies
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Data Quality engineer

Data Quality engineer

Algoleap Technologies

1 - 4 years

3 - 6 Lacs

hyderabad

Posted:5 hours ago| Platform:

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Skills Required

data validation agile data quality test cases downstream crm auditing sql salesforce marketing automation

Work Mode

Work from Office

Job Type

Full Time

Job Description

Define and execute validation strategies for data pipelines, integrations, and transformations across Segment, SFMC, Snowflake, and downstream dashboards.

Create and maintain automated data quality checks, test scripts, and regression suites to validate accuracy, completeness, and consistency of data.

Support adoption of Trust the Data framework and ensure alignment with Medallion architecture (Bronze Silver Gold views).

Validate logic used for user segmentation, lead qualification and such marketing activities

Partner with Product Managers and Data Engineering teams to define acceptance criteria and test coverage for user stories in ADO/Jira.

Work with product manager to ensure validated data supports marketing KPIs (campaign ROI, funnel conversion, lead quality, data accuracy %).

Support onboarding of priority datasets into SODA DQ Scorecards and assist in interpreting data quality scores.

Maintain test documentation, validation reports, and sign-offs for compliance and audit readiness.

Required Skills

Strong SQL skills for validating complex datasets in Snowflake (joins, aggregations, lineage checks).

Hands-on experience with data validation frameworks (e.g., SODA).

Familiarity with ETL/ELT workflows and validation of data pipelines.

Exposure to marketing technology platforms (Segment, Salesforce Marketing Cloud, or similar CDPs/marketing automation tools).

Ability to design comprehensive data test cases for completeness, accuracy, consistency, and timeliness.

Strong problem-solving skills to identify root causes of data discrepancies and recommend remediation steps.

Experience working with Medallion architecture (Bronze/Silver/Gold layers) and canonical data views.

Strong written and verbal communication to translate technical data validation results into business-impact insights.

Comfortable working in cross-functional teams with Product Managers, Data Engineers, Marketing stakeholders, and vendors.

Experience with agile environments and tools like ADO, Jira, Confluence, Git.

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Data Quality engineer