Analyst I - Data Analytics

Darwinbox Digital Solutions Pvt. Ltd.; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Darwinbox Digital Solutions Pvt. Ltd. is seeking a Senior Data Analyst to perform complex analytical work and own major deliverables that support HR analytics products and business decisions.

You will collaborate with HR Analytics leaders, BAs, SMEs, and tech partners to translate requirements into data needs and acceptance criteria. You will independently develop, validate, and document deliverables, identify data limitations, and provide guidance to ensure accuracy and fitness for use.

Qualifications

• Bachelor’s degree in Business, HR, Information Systems, Computer Science, Data Analytics, Statistics, Engineering, or a related field.
• Five or more years of relevant experience in data analysis, analytics engineering, or a related discipline.
• Advanced experience using SQL and Python to prepare, analyze, validate, and reconcile complex data; proficiency with Excel and data-modeling fundamentals.

Responsibilities

• Own end-to-end delivery of higher-complexity analyses and data workstreams.
• Lead major deliverables with limited oversight and translate business needs into data requirements.
• Identify delivery risks and data limitations early and propose mitigation actions.
• Review analytical deliverables for validity, accuracy, completeness, and governance alignment.
• Provide technical guidance, peer review, and mentoring to analysts to uphold standards.
• Develop reusable analytical methods, templates, and quality practices.

Skills

Advanced SQL

Python

Data analysis

Education

Bachelor’s degree in related field

5+ years of data analysis experience

Tools

SQL

Python

Job description

The Senior Data Analyst performs complexanalytical data work and owns major deliverables or defined workstreams thatsupport HR analytics products and business decision-making. This role workswith HR Analytics leaders, Business Analysts, subject matter experts, andtechnical partners to resolve ambiguity, translate requirements intotechnical data needs, business rules, calculations, and acceptance criteria,and determine appropriate analytical approaches.

The Senior Data Analyst independentlydevelops, validates, and documents analytical deliverables; identifies risks,dependencies, assumptions, and data limitations; and reviews outputs foraccuracy, completeness, and fitness for use. The role requires advancedanalytical and technical capability, independent judgment, and the ability toprovide technical guidance and contribute to reusable methods, standards,documentation, and quality practices.

Responsibilities

Senior-Level Ownership & DeliveryLeadership

• Ownthe end-to-end delivery of higher-complexity analyses, analytical datasets,and defined data workstreams, from source assessment and technical designthrough development, validation, release, ongoing support, enhancement, andretirement where applicable.
• Lead major deliverables ordefined workstreams with limited oversight, working with HR Analyticsleaders, Business Analysts, subject matter experts, and technical partners totranslate clarified business needs into scope, data requirements, successmeasures, technical outputs, delivery plans, and recommendations.
• Establishand manage priorities for assigned deliverables while balancing newdevelopment with data reliability, production support, reusable solutiondesign, and reduction of technical debt.
• Identifydelivery risks, data limitations, technical dependencies, requirement gaps,and alignment issues early and recommend practical mitigation actions.
• Reviewanalytical deliverables before release for analytical validity, technicalaccuracy, completeness, data quality, traceability, governance alignment,fitness for use, and operational supportability.
• Providetechnical guidance, peer review, and mentoring to less experienced analystswhile reinforcing documentation, testing, validation, and developmentstandards.

Data Analysis & Analytical Delivery

• Extract,clean, transform, combine, and validate complex HR, workforce, operational,product, and transformation data from approved sources.
• Perform advanced descriptive,diagnostic, variance, trend, segmentation, root-cause, and other analyses toaddress complex business questions.
• Developand validate complex analytical datasets, summaries, tables, charts, and recommendations that support analytics products and decision-making.
• Useadvanced SQL, Python, and approved analytical tools to develop repeatable,efficient, maintainable, and well-tested analytical processes.
• Interpret complex results,distinguish supported conclusions from uncertainty, and explain findings,risks, limitations, and practical implications.

Data Requirements & Solution Support

• Workwith HR Analytics leaders, Business Analysts, subject matter experts, andtechnical partners to resolve ambiguity and refine complex analytical anddata requirements.
• Translateclarified requirements into detailed data needs, calculations, mappings,business rules, acceptance criteria, and technical approaches.
• Assessunfamiliar or complex source data to determine its availability, structure,grain, quality, completeness, limitations, dependencies, and fitness for use.
• Developand maintain major analytical datasets, data models, and reusable datastructures within assigned workstreams.
• Partner with BI developers, dataengineers, data quality teams, and other technical partners to resolvedependencies and ensure data outputs support approved analytical andreporting use cases.

Metric Support, Data Quality & Validation

• Defineand validate metric definitions, calculations, filters, cohorts, and businessrules for complex analyses and assigned data workstreams.
• Establishand perform comprehensive data-quality, reconciliation, and validationprocedures for complex deliverables.
• Planand oversee data-focused testing, including test scenarios, expected results,reconciliation, defect documentation, retesting, and release validation.
• Investigatecomplex data discrepancies, identify root causes and downstream impacts, andimplement or coordinate durable corrective actions with appropriate partners.
• Document material assumptions,data limitations, quality concerns, unresolved issues, and validationresults.

Stakeholder Partnership & Communication

• Partnerwith HR Analytics leaders, Business Analysts, subject matter experts, andtechnical partners throughout delivery to refine analytical questions, metriclogic, acceptance criteria, and expected outputs.
• Communicatedelivery status, recommendations, assumptions, risks, dependencies, datalimitations, and timelines clearly to technical and nontechnicalstakeholders.
• Presentcomplex analytical findings in a clear, concise, and actionable mannerwithout overstating what the data supports.

Documentation, Standards & OperationalSupport

• Createand maintain comprehensive documentation for data sources, requirements,mappings, metric definitions, business rules, calculations, transformationlogic, testing, dependencies, lineage, and known limitations.
• Applyand reinforce established practices for version control, peer review, modulardevelopment, testing, deployment, release management, documentation,security, privacy, and data governance.
• Developreusable analytical methods, templates, standards, and quality practices thatimprove consistency, scalability, maintainability, and delivery efficiency.
• Supportdeployment, post-release validation, production issue investigation, andongoing maintenance in collaboration with appropriate technical partners.
• Protect confidential HR andworkforce information through approved access controls, data-handlingpractices, security requirements, and privacy and compliance standards.

AI-Assisted Analytics

• Useapproved AI-enabled tools to accelerate complex data exploration, codedevelopment, documentation, data profiling, test development, quality review,and insight summarization.
• Criticallyevaluate and independently validate AI-assisted code, calculations,interpretations, and outputs against approved data, source documentation, andestablished requirements.
• Identifyand address risks associated with AI-assisted analysis, including unsupportedconclusions, bias, data exposure, inadequate testing, and insufficientbusiness context.
• Developor contribute to reusable and responsible AI-assisted analytical methods,documentation, controls, and quality practices.
• Follow responsible AI, privacy,security, and HR-data handling requirements, including restrictions onentering confidential or restricted information into unapproved tools.

Education & Experience:

• Bachelor’s degree in Business, HumanResources, Information Systems, Computer Science, Data Analytics, Statistics,Engineering, or a related field; an equivalent combination of education andexperience may be considered.
• Five or more years of relevant experience indata analysis, business intelligence, analytics engineering, or a relateddiscipline.
• Advanced experience using SQL and Python toprepare, analyze, validate, and reconcile complex data; proficiency withExcel and working knowledge of data-modeling fundamentals.
• Experience working with cloud-based analyticalplatforms or distributed databases.
• Experience leading complex analyses, majordeliverables, or defined workstreams with limited oversight, includingmanaging dependencies, identifying risks, validating outputs, andcommunicating recommendations.
• Experience reviewing analytical deliverables,mentoring others, and contributing to reusable methods, documentation,standards, or quality practices.
• Experience handling confidential data inaccordance with privacy, security, governance, and responsible-AIrequirements.

Nice to Have Skills

• Experience with HR or workforce data andplatforms such as Workday, Oracle HCM, or PeopleSoft.
• Experience in healthcare, HR transformation,shared services, global capability centers, or other regulated environments.
• Experience with statistical analysis, datavisualization, survey analysis, product analytics, or process analytics.
• Experience applying approved AI tools to dataprofiling, code generation, documentation, quality checks, analysis, orstakeholder communication.

Licenses, Certifications & Training:

• Preferred:role-relevant certification, analytics platform training, data governancetraining, or Agile delivery training, as applicable.
• Preferred:Responsible AI, data privacy, data security, or HR data handling training.

Knowledge, Skills, Abilities, Behaviors:

• Ability to independently structure and executecomplex analytical work, resolve ambiguity, and exercise sound judgment.
• Ability to evaluate analytical methods anddeliverables for accuracy, completeness, data quality, business relevance,and fitness for use.
• Ability to identify and communicateassumptions, risks, dependencies, data limitations, and unsupportedconclusions.
• Ability to translate complex analyticalfindings into clear, concise, and actionable information for technical andnontechnical audiences.
• Ability to collaborate effectively with HRAnalytics leaders, Business Analysts, subject matter experts, and technicalpartners in a matrixed environment.
• Ability to manage competing priorities,maintain delivery discipline, and elevate issues with practicalrecommendations.
• Ability to provide constructive technicalguidance, peer review, and mentoring while reinforcing documentation,testing, and quality standards.
• Ability to protect confidential HR andworkforce information and apply privacy, security, governance, andresponsible-AI requirements.