Data Analyst - Validation

Full-time role only - US Citizens / GC Holders are required - Should apply. HCLTech is looking for a highly talented and self- motivated Data Analyst & Validation Engineer (ETL QA Focused). Only US Citizens or GC holders requiredFull time role) to join it in advancing the technological world through innovation and creativity.Key ResponsibilitiesMust have Skills - 6-10 years Data Validation & Validation & AWS Data services (Redshift, Lake Formation, Athena, and S3-based data lakes), Python, ETL ELT concepts, QA methodology (Test planning & design, Defect lifecycled.Data Validation & VerificationValidate transformation logic against business rules and documented specificationsPerform source-to-target data reconciliation — verifying completeness, accuracy, and consistencyIdentify data anomalies, silent failures, and drift in pipeline outputsBuild and maintain automated data validation suites that execute as part of pipeline runsConduct periodic data audits beyond automated checksQA Process Definition & GovernanceDefine acceptance criteria for each ETL pipeline and transformation step — establishing what "correct" means in measurable, testable termsDefine Definition of Done (DoD) for all data deliverables — specifying when a pipeline output is considered production-readyCreate and maintain data quality test plans covering functional correctness, edge cases, regression, and performanceDesign test cases for new transformations before they reach production (shift-left testing)Establish data quality SLAs — freshness, completeness, and accuracy thresholdsDefine entry and exit criteria for pipeline releases — what must pass before promoting changesMaintain a defect taxonomy — categorizing data issues (schema drift, logic errors, source issues, timing issues) for root cause tracking and trend analysisDefine sign-off workflows — who approves what before data reaches the UI layerTest Strategy & FrameworksDesign the overall data testing strategy:Unit tests for individual transformation logicIntegration tests for end-to-end pipeline correctnessRegression tests for ongoing stabilitySmoke tests for post-deployment verificationNegative tests for resilience (nulls, duplicates, out-of-range values, schema violations)Build reusable, parameterized validation patterns applicable across multiple pipelinesImplement data contract validation — ensuring upstream sources meet agreed schemas and value constraintsIntegrate quality gates into CI/CD pipelines for automated release blockingDocumentation & TraceabilityDocument expected behavior for each transformation (input, logic, expected output)Maintain data quality runbooks — investigation and resolution procedures for common issuesCreate traceability matrices linking business requirements to test cases to pipeline outputsDocument known data limitations, assumptions, and technical debtMaintain a living catalog of data quality rules and their rationaleMonitoring, Observability & ReportingBuild data quality dashboards tracking pass/fail rates, trend analysis, and SLA complianceConfigure alerting for data quality threshold breachesTrack and report data quality metrics (DQ score, defect density, mean time to detect, mean time to resolve)Conduct data quality retrospectives — identifying gaps and improving coverageCollaborationParticipate in pipeline design reviews — flagging quality risks early in developmentWork with product and business stakeholders to translate vague requirements into testable assertionsCollaborate with data engineers on pipeline improvements driven by quality findingsSupport UI/frontend teams in verifying rendered data correctnessRequired QualificationsTechnical SkillsAreaRequirementSQLAdvanced — window functions, CTEs, set comparisons, complex joins, data profiling queriesAWS Data ServicesHands-on experience querying and validating data in Amazon Redshift, AWS Lake Formation, Athena, and S3-based data lakesPython (or equivalent scripting)Validation scripts, data comparison tools, automation frameworksETL/ELT ConceptsDeep understanding of extraction, transformation, and loading patterns, including common failure modesQA MethodologyTest planning, test case design, acceptance criteria definition, defect lifecycle managementData ProfilingStatistical profiling, distribution analysis, completeness and uniqueness checksValidation FrameworksHands-on experience with at least one: Great Expectations, dbt tests, Soda Core, or equivalent custom frameworksVersion ControlGit — managing test suites alongside pipeline codeExperience6-10 years of combined experience in data engineering, data QA, or analytics engineeringHas owned data quality for at least one production system end-to-end (not just contributed)Has defined acceptance criteria and quality gates that blocked defective releasesHas built automated validation suites that caught real production issuesComfortable reading and reasoning about pipeline code (transformation logic, orchestration DAGs)Experience working with curated/aggregated datasets that serve application UIsFamiliarity with AWS Glue, Redshift Spectrum, and AWS data pipeline servicesPreferred ExperienceExperience with BDD-style data testing (Given/When/Then for data transformations)CI/CD integration for data quality — automated gates in deployment pipelinesExperience defining and tracking data SLAs/SLOsKnowledge of regulatory or compliance data requirementsPerformance testing for pipelines — verifying latency and throughputExposure to chaos engineering for data — intentionally injecting bad data to test resilienceExperience with pipeline orchestration tools (Glue Orchestrator, Step Functions, Airflow)Experience with IAM permissions and Lake Formation access controls for data governancePay Range Minimum: 69000Pay Range Maximum: 128000HCLTech is an equal opportunity employer, committed to providing equal employment opportunities to all applicants and employees regardless of race, religion, sex, color, age, national origin, pregnancy, sexual orientation, physical disability or genetic information, military or veteran status, or any other protected classification, in accordance with federal, state, and/or local law. Should any applicant have concerns about discrimination in the hiring process, they should provide a detailed report of those concerns to secure@hcltech.com for investigation. A candidate’s pay within the range will depend on their skills, experience, education, and other factors permitted by law. This role may also be eligible for performance-based bonuses subject to company policies. In addition, this role is eligible for the following benefits subject to company policies: medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance; employee assistance program; 401(k) retirement plan; 10 days of paid time off per year (some positions are eligible for need-based leave with no designated number of leave days per year); and 10 paid holidays per yearHow You’ll GrowAt HCLTech, we offer continuous opportunities for you to find your spark and grow with us. We want you to be happy and satisfied with your role and to really learn what type of work sparks your brilliance the best. Throughout your time with us, we offer transparent communication with senior-level employees, learning and career development programs at every level, and opportunities to experiment in different roles or even pivot industries. We believe that you should be in control of your career with unlimited opportunities to find the role that fits you best.