Sr. Business Analyst – With HR Data Domain Knowledge

Important Candidate Submission Requirements

• A valid LinkedIn profile is mandatory and must be included when submitting the resume.

• Face-to-Face (F2F) interview is mandatory. Candidates must be local or fully committed to attending the in-person interview as required.

• Please do not submit candidates who do not meet all of the above requirements.

• This is a senior role with 12+ exp acting as a key liaison between HR/business stakeholders and Data Engineering/Technology teams, translating complex business requirements into clear technical specifications, data mappings, transformation rules, and analytical solutions. Support enterprise HR data initiatives within the Life Insurance domain by ensuring business requirements are accurately understood, technically implemented, validated, and delivered.

  Key Responsibilities

  • Act as the primary bridge between HR business teams and Data Engineering/Technology teams for HR data, analytics, reporting, and integration initiatives.
  • Partner with HR, Finance, Operations, Risk, Compliance, and Technology stakeholders to understand business objectives and translate them into actionable technical requirements.
  • Conduct requirement-gathering sessions and document business requirements, functional requirements, data requirements, source-to-target mappings, business rules, and acceptance criteria.
  • Translate business terminology and HR processes into technical specifications that data engineers, developers, architects, and BI teams can implement.
  • Analyze HR datasets including employee, position, organizational hierarchy, compensation, payroll, benefits, recruiting, performance, termination, and workforce planning data.
  • Perform detailed data profiling, mapping, lineage analysis, gap analysis, and source-system analysis.
  • Develop and execute complex SQL queries to investigate data, validate business rules, reconcile source and target systems, and troubleshoot production issues.
  • Convert business rules into detailed transformation logic, for example: HR Source → Business Rule → Transformation → Enterprise Data Model → Reporting Metric.
  • Validate engineering implementations against documented requirements and ensure delivered datasets accurately represent business expectations.
  • Perform source-to-target validation, reconciliation, regression testing, system integration testing, and UAT support.
  • Investigate discrepancies between HR source systems, enterprise data platforms, Finance systems, and management reports.
  • Facilitate defect triage between business and engineering teams, determine root causes, clarify expected behavior, and coordinate resolution.
  • Maintain data dictionaries, mapping documents, business glossaries, lineage documentation, technical specifications, and process flows.
  • Support Agile delivery by developing/refining user stories, acceptance criteria, backlog items, dependencies, and technical requirements.
  • Build or support Tableau/Power BI dashboards and analytical datasets used for executive workforce reporting and decision-making.
  • Communicate technical issues in business-friendly language while translating business expectations into sufficient technical detail for engineering teams