Data Analyst (Snowflake / SQL)

We are looking for a Data Analyst (Snowflake / SQL) to support data analysis, data profiling, lineage validation, reporting, and regulatory data initiatives. The role will involve working with large and complex datasets in Snowflake, analyzing source-to-target data flows, validating report and data lineage, identifying data quality issues, and supporting the onboarding and maintenance of regulatory reports.

The ideal candidate should have strong SQL and data analysis capabilities, a good understanding of data flows and lineage, and the ability to work with both business and technical stakeholders to investigate data issues and translate reporting requirements into actionable data requirements.

• Analyze data across source systems, transformation layers, data warehouses, and reporting platforms using advanced SQL.

• Perform data profiling, validation, reconciliation, and exploratory analysis to understand data structures, relationships, completeness, and quality.

• Analyze and validate source-to-target mappings, ensuring that data is correctly mapped through different stages of the data flow.

• Validate report-to-source lineage, including the flow of data from source systems through transformations to final reports.

• Trace data elements across systems to support impact analysis, issue investigation, and regulatory reporting requirements.

• Support the onboarding of new regulatory reports by analyzing data requirements, source systems, mappings, transformations, and reporting logic.

• Review existing reports and data flows to identify lineage gaps, inconsistencies, or undocumented transformations.

• Perform data quality assessments and investigate issues related to completeness, accuracy, consistency, timeliness, and validity.

• Conduct root cause analysis for data and reporting issues and work with technology and business teams to identify appropriate remediation.

• Develop SQL queries and analytical outputs to support data investigations, reporting requirements, and governance activities.

• Create and maintain analytical metrics, operational reports, and dashboards to communicate data quality and reporting outcomes.

• Support audit, risk, compliance, and regulatory reporting activities, including data validation and evidence preparation.

• Interpret business requirements, reporting specifications, and BRDs and translate them into data and analytical requirements.

• Work closely with Data Analysts, Business Analysts, Data Engineers, Data Governance teams, Report Owners, and business stakeholders.

• Document data findings, mappings, lineage, business rules, analytical logic, and issue-resolution outcomes.

• Contribute to continuous improvement of data analysis, reporting, and data quality processes.

• Strong hands-on experience with SQL, including complex joins, subqueries, CTEs, aggregations, window functions, and data validation queries.

• Experience working with Snowflake or a comparable cloud data warehouse.

• Strong experience in data analysis and data profiling.

• Understanding of data lineage, data flows, source-to-target mappings, and data transformations.

• Experience investigating data quality issues and performing root cause analysis.

• Ability to analyze large datasets andidentifypatterns, anomalies, inconsistencies, and data gaps.

• Experience working with business and technical requirements and interpreting BRDs, reporting specifications, and data requirements.

• Good understanding of reporting and data processes within enterprise environments.

• Experience supporting regulatory reporting, risk, compliance, or audit-related data activities is preferred.

• Strong documentation and communication skills.

• Ability to collaborate effectively with technical teams, business users, data owners, and reporting stakeholders.

• Experience with Power BI or other BI/reporting tools.

• Experience working with regulatory reporting datasets and controls.

• Exposure todata governance, metadata management, or data catalog platforms.

• Experience with financial services, banking, insurance, or other highly regulated industries.

• Knowledge of ETL/ELT concepts and modern cloud data architectures.

• Familiarity with data reconciliation and control frameworks.

Originally posted on Himalayas