{"id":3168790,"url":"https://alion.io/job/zensar-technologies-sr-data-engineer","title":"Sr. Data Engineer","company":{"id":59576,"name":"Zensar Technologies","domain":"zensar.com","url":"https://alion.io/company/zensar-technologies","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":86,"open_postings":44,"ghost_share":0.182,"stale_share":0.091,"repost_share":0.386,"time_to_fill_p50_days":5,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":41000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Matillion","optional":false},{"name":"Rest API","optional":false},{"name":"Snowflake","optional":false},{"name":"SOAP","optional":false},{"name":"SQL","optional":false},{"name":"Talend","optional":false},{"name":"Amazon S3","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Dimensional Modeling","optional":true}],"status":"live","first_seen_at":"2026-10-22T13:01:11Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-10-25T02:30:37Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Key Responsibilities\nDesign, develop, and maintain scalable data ingestion, transformation, and integration pipelines.\nAnalyze, diagnose, and resolve DQCI (Data Quality & Critical Issues) remediation requirements across the data ecosystem.\nImplement fixes across ingestion, transformation, and consumption layers to ensure data accuracy and consistency.\nPerform root-cause analysis of data defects and implement sustainable long-term solutions.\nDevelop and optimize ETL/ELT processes using industry-leading data integration tools.\nBuild and enhance data pipelines to support business intelligence, reporting, analytics, and downstream applications.\nDevelop complex data transformation and mapping logic to meet business requirements.\nIntegrate data from multiple internal and external systems through APIs and batch interfaces.\nOptimize SQL queries, database objects, and data processing workloads for performance and scalability.\nCollaborate with business, analytics, and architecture teams to ensure high-quality data delivery.\nSupport DevOps and CI/CD practices for deployment, version control, and release management.\nEnsure adherence to data governance, security, and compliance standards.\nRequired Technical Skills\nCore Skills\nSnowflake DevelopmentData modeling and schema design\nPerformance tuning and optimization\nStored procedures, tasks, streams\n\nMatillion ETL/ELTJob orchestration\nData transformation and workflow development\nIntegration with Snowflake and cloud platforms\n\nTalend Data IntegrationETL development\nData migration and integration solutions\nData quality and validation frameworks\n\nAdvanced SQLComplex joins, stored procedures, views, and performance optimization\nQuery tuning and large-scale data processing\n\nData PipelinesBatch and near real-time processing pipelines\nData ingestion, transformation, and orchestration\n\nData Transformation & MappingSource-to-target mappings\nBusiness rule implementation\nData reconciliation\n\nAPI IntegrationREST/SOAP APIs\nAPI-based data ingestion and integration\n\nAzure DevOpsSource control management\nCI/CD pipeline and deployment\nRelease management and automation\n\nExpected Contributions\nDiagnose and resolve DQCI remediation work across enterprise data platforms.\nImplement fixes across ingestion and transformation pipelines to eliminate recurring data issues.\nCorrect defects at source, integration, or consumption layers based on root-cause analysis.\nImprove overall platform stability, reliability, and data quality.\nDeliver sustainable and scalable fixes rather than temporary workarounds.\nOptimize existing ETL/ELT processes and improve pipeline performance.\nSupport production issues and provide timely resolution of critical data incidents.\nEnsure data accuracy, completeness, and consistency across systems.\nCollaborate effectively with Data Architects, Business Analysts, QA teams, and stakeholders.\nContribute to continuous improvement initiatives and engineering best practices.\nPreferred Qualifications\nStrong Experience with Talend + Snowflake + Matillion + Postgress\nHands on experience on AWS and S3\nStrong knowledge of data warehousing concepts, dimensional modeling, and data governance.\nExperience working in Data warehousing projects & agile\nStrong analytical, troubleshooting, and problem-solving skills.\nTarget Designation: Senior Data Engineer\nLocation Preference: Offshore\nPrimary Skills: Talend, Snowflake, Advanced SQL, Matillion, Data Pipeline Engineering, Data warehousing.\nSecondary Skills: Postgress, API integration, AWS, Matillion, Azure DevOps\nOK\n 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