{"id":3773704,"url":"https://alion.io/job/zensar-technologies-data-engineering-offshore","title":"Data Engineering offshore","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":91,"open_postings":70,"ghost_share":0.1,"stale_share":0.086,"repost_share":0.386,"time_to_fill_p50_days":6,"computed_at":"2026-11-07T05:47:08Z"}},"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":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache HTTP Server","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"MS SQL","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"SSIS","optional":false},{"name":"Machine Learning","optional":true},{"name":"Power BI","optional":true}],"status":"live","first_seen_at":"2026-11-04T17:38:53Z","employer_posted_date":"2026-11-04","last_verified_at":"2026-11-07T12:33:11Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"As a Senior Data Engineer, you will:\nDesign, develop, and support scalable batch and near real-time data pipelines, data products, and lakehouse-ready data assets using Spark, Python, SQL, Hive, Databricks, and cloud-native technologies.\nBuild and optimize capabilities supporting the ONE Data Lake and Mastercard's unified data platform strategy.\nDevelop ingestion, transformation, and orchestration solutions for batch and streaming/near real-time data patterns using technologies such as Cribl, SSIS, Apache Ozone, Cloudera Data Services, Hive, Spark, Azure, Microsoft Fabric, Databricks, and related ecosystem tools.\nEnable trusted, governed, and accessible enterprise data through the implementation of data quality, lineage, and governance standards.\nPartner closely with Product, TPM, Data Governance, Architect, and Engineering teams to deliver strategic business outcomes.\nSupport AI, analytics, reporting, and decisioning use cases by delivering scalable and reliable data assets.\nDrive modernization initiatives across hybrid data environments and cloud.\nImprove operational efficiency through automation, monitoring, observability, and self-service capabilities.\nTroubleshoot complex platform and data issues, perform root cause analysis, and implement sustainable solutions.\nEvaluate emerging technologies and identify opportunities to advance Team ONE's data capabilities.\nRequired Qualifications\n6+ years of experience delivering enterprise-scale data engineering, data warehousing, or big data solutions.\nStrong hands-on experience with Apache Spark, Python, SQL and Databricks.\nExperience building and maintaining large-scale data pipelines and distributed data processing systems.\nExperience with streaming or near real-time ingestion patterns, including event/log data collection, routing, transformation, and delivery into enterprise data lake or lakehouse platforms.\nExperience with Hive, Apache Ozone, or similar data integration, Azure, Microsoft Fabric, and orchestration technologies.\nStrong understanding of data architecture, ETL/ELT design patterns, and modern data platform principles.\nHands-on experience with Microsoft SQL Server, SSIS packages, stored procedures, SQL performance tuning, and relational database concepts.\nExperience implementing data quality, governance, metadata, and lineage capabilities.\nProven ability to analyze complex production issues, perform root cause analysis, and implement long-term solutions.\nStrong communication and collaboration skills with the ability to work effectively across technical and business teams.\nDemonstrated ability to manage competing priorities in a fast-paced environment.\nStrong ownership mindset and commitment to delivering high-quality solutions.\nAs a Senior Data Engineer, you will:\nDesign, develop, and support scalable batch and near real-time data pipelines, data products, and lakehouse-ready data assets using Spark, Python, SQL, Hive, Databricks, and cloud-native technologies.\nBuild and optimize capabilities supporting the ONE Data Lake and Mastercard's unified data platform strategy.\nDevelop ingestion, transformation, and orchestration solutions for batch and streaming/near real-time data patterns using technologies such as Cribl, SSIS, Apache Ozone, Cloudera Data Services, Hive, Spark, Azure, Microsoft Fabric, Databricks, and related ecosystem tools.\nEnable trusted, governed, and accessible enterprise data through the implementation of data quality, lineage, and governance standards.\nPartner closely with Product, TPM, Data Governance, Architect, and Engineering teams to deliver strategic business outcomes.\nSupport AI, analytics, reporting, and decisioning use cases by delivering scalable and reliable data assets.\nDrive modernization initiatives across hybrid data environments and cloud.\nImprove operational efficiency through automation, monitoring, observability, and self-service capabilities.\nTroubleshoot complex platform and data issues, perform root cause analysis, and implement sustainable solutions.\nEvaluate emerging technologies and identify opportunities to advance Team ONE's data capabilities.\nRequired Qualifications\n6+ years of experience delivering enterprise-scale data engineering, data warehousing, or big data solutions.\nStrong hands-on experience with Apache Spark, Python, SQL and Databricks.\nExperience building and maintaining large-scale data pipelines and distributed data processing systems.\nExperience with streaming or near real-time ingestion patterns, including event/log data collection, routing, transformation, and delivery into enterprise data lake or lakehouse platforms.\nExperience with Hive, Apache Ozone, or similar data integration, Azure, Microsoft Fabric, and orchestration technologies.\nStrong understanding of data architecture, ETL/ELT design patterns, and modern data platform principles.\nHands-on experience with Microsoft SQL Server, SSIS packages, stored procedures, SQL performance tuning, and relational database concepts.\nExperience implementing data quality, governance, metadata, and lineage capabilities.\nProven ability to analyze complex production issues, perform root cause analysis, and implement long-term solutions.\nStrong communication and collaboration skills with the ability to work effectively across technical and business teams.\nDemonstrated ability to manage competing priorities in a fast-paced environment.\nStrong ownership mindset and commitment to delivering high-quality solutions.\nRequired Qualifications\n6+ years of experience delivering enterprise-scale data engineering, data warehousing, or big data solutions.\nStrong hands-on experience with Apache Spark, Python, SQL and Databricks.\nExperience building and maintaining large-scale data pipelines and distributed data processing systems.\nExperience with streaming or near real-time ingestion patterns, including event/log data collection, routing, transformation, and delivery into enterprise data lake or lakehouse platforms.\nExperience with Hive, Apache Ozone, or similar data integration, Azure, Microsoft Fabric, and orchestration technologies.\nStrong understanding of data architecture, ETL/ELT design patterns, and modern data platform principles.\nHands-on experience with Microsoft SQL Server, SSIS packages, stored procedures, SQL performance tuning, and relational database concepts.\nExperience implementing data quality, governance, metadata, and lineage capabilities.\nProven ability to analyze complex production issues, perform root cause analysis, and implement long-term solutions.\nStrong communication and collaboration skills with the ability to work effectively across technical and business teams.\nDemonstrated ability to manage competing priorities in a fast-paced environment.\nStrong ownership mindset and commitment to delivering high-quality solutions.\nPreferred Qualifications\nExperience with Cribl or similar observability/log streaming platforms, including data routing, filtering, enrichment, and delivery to downstream lakehouse or analytics platforms.\nExperience with Microsoft Fabric, OneLake, and cloud-native data platforms.\nExperience with enterprise data governance and metadata management solutions.\nExperience supporting analytics, reporting, AI, or machine learning workloads.\nExperience with Power BI and enterprise reporting environments.\nExperience mentoring engineers and leading technical initiatives.","description_format":"text","description_chars":7388,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams"],"lifecycle":[{"event":"open","at":"2026-11-04T22:27:45Z"}],"visa":[],"liveness":{"score":81,"band":"hot","label":"Hiring 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