Sr. Data Analyst

Position Summary- Must be a US Citizen or Green Card Holder

The Senior Data Analyst is a lead individual contributor responsible for ensuring the accuracy, consistency, and enterprise readiness of the organization’s data assets. This role supports data onboarding, analysis, reconciliation, and validation, and is responsible for communicating and documenting findings and insights for both technical and non‑technical stakeholders. The role covers existing datasets and new data domains as they are introduced, including benefits, billing, finance/accounting and planning, investments, and affiliated markets data from enterprise systems such as Salesforce, Workday, Dynamo, BNY Mellon, and others.

The Senior Data Analyst works independently on complex datasets, leads data onboarding and data validation efforts, and serves as a key bridge between Data Engineering, Enterprise Analytics \& Reporting, and various business stakeholders ensuring that data used by reports, dashboards, and analytics is trusted, well‑defined, and audit‑defensible.

Key Responsibilities

• Own data validation, reconciliation, and readiness standards for all enterprise and cross-domain datasets.
• Lead onboarding and certification of new data sources, ensuring accuracy, completeness, and consistency of historical, incremental, and future data in data warehouse.
• Serve as the primary escalation point for complex or recurring data quality issues.
• Apply and support the enterprise data stewardship principles according to the data governance policies.
• Collaborate with enterprise and cross-domain stakeholders to understand requirements and define data quality rules, acceptance criteria, and data lineage expectations.
• Lead data exploration and profile for the incoming source data.
• Analyze complex, multi‑source datasets to support operational, financial, and strategic reporting.
• Translate the data requirements into clear data definitions and validation logic for data engineering to develop the data transformation pipeline jobs.
• Lead root‑cause analysis of data defects and drive permanent corrective actions.
• Build reusable validation queries for data trend patterns to improve data consistency and efficiency.
• Partner with Data Engineering to automate data quality checks and monitoring.
• Establish and maintain certified, reporting‑ready datasets for enterprise and cross-domain uses.
• Lead the data validation process across QA, UAT, and post‑deployment phases.
• Communicate the data impacts of the new release to downstream systems and users.
• Own creation and maintenance of data dictionaries, lineage, data scenarios, metrics calculation logic, and business rules documentation for all datasets available in data warehouse.
• Contribute to data cataloging and metadata management to improve discoverability and governance.

Required Qualifications

• Bachelor’s degree in Data Analytics, Information Systems, Computer Science, or a related field (or equivalent experience).
• 5–8 years of experience in enterprise data analytics or data warehousing environments.
• Advanced SQL expertise, including complex joins, CTEs, window functions, and query optimization.
• Experience validating ELT/ETL pipelines and complex data transformations.
• Strong experience working with governed, multi‑source enterprise data.

Preferred Qualifications

• Experience supporting enterprise platforms such as HR and benefits, CRM, financial, pension, and market data systems.
• Experience with Snowflake SQLs and other features is plus.
• Familiarity with modern cloud data platforms and data governance tooling.
• Experience operating in audit‑sensitive or regulated environments.
• Scripting experience (e.g. PL/SQL, Python, etc.) for data validation or analysis.
• Prior experience mentoring analysts or leading standards development.