{"id":2923106,"url":"https://alion.io/job/evolutyz-corp-data-engineer","title":"Data Engineer","company":{"id":20438,"name":"Evolutyz Corp","domain":"evolutyz.com","url":"https://alion.io/company/evolutyz-corp","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":42000,"period":"year","method":"role_seniority_country_cell","sample_n":77},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Microsoft Entra ID","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"closed","first_seen_at":"2026-10-20T12:37:00Z","employer_posted_date":null,"last_verified_at":"2026-10-24T17:36:15Z","board_verified":false,"closed_at":"2026-10-24T17:36:15Z","days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Microsoft Azure Data Engineer to join a growing data and analytics team. The ideal candidate will have strong hands-on experience with Microsoft Azure data services, Azure Synapse Analytics and/or Microsoft Fabric, data engineering, data integration, data transformation, and enterprise data platforms. The role is responsible for designing, developing, implementing, and optimizing scalable data pipelines, data warehouses, lakehouses, and enterprise data solutions using the Microsoft Azure data ecosystem. This role will work closely with data architects, Power BI developers, analysts, software engineers, DevOps engineers, and business stakeholders to build reliable, scalable, secure, and high-performing enterprise data platforms.\n\nResponsibilities: \nDesign, develop, and maintain enterprise data solutions using Microsoft Azure.\nBuild scalable data ingestion, transformation, and processing solutions.\nDevelop and optimize data pipelines using Azure Data Factory, Azure Synapse Analytics, and/or Microsoft Fabric.\nDesign solutions that integrate data from databases, APIs, files, SaaS platforms, cloud applications, and enterprise systems.\nDevelop reusable data engineering frameworks and components.\nImplement batch and near-real-time data processing solutions.\nMonitor, troubleshoot, and optimize Azure data workloads.\nSupport modernization and migration of legacy data platforms to Azure.\nDesign and develop data solutions using Azure Synapse Analytics and/or Microsoft Fabric.\nBuild enterprise data warehouses and Lakehouse solutions.\nDevelop data pipelines and orchestration workflows.\nWork with Synapse Pipelines, Fabric Data Factory, and Azure Data Factory.\nDevelop notebooks using Python, PySpark, and Spark SQL.\nBuild and optimize data transformation processes.\nWork with Synapse SQL, Fabric Data Warehouse, Fabric Lakehouse, and related technologies.\nSupport migration and modernization initiatives between traditional Azure architectures, Azure Synapse, and Microsoft Fabric.\nEvaluate appropriate technologies based on performance, scalability, cost, security, and business requirements.\nDesign and develop robust ETL and ELT pipelines.\nIngest structured, semi-structured, and unstructured data from multiple enterprise sources.\nIntegrate data from databases, APIs, files, SaaS applications, and cloud platforms.\nDevelop reusable ingestion and transformation frameworks.\nImplement incremental data loads and Change Data Capture (CDC) strategies.\nDevelop data validation, reconciliation, and error-handling processes.\nTroubleshoot pipeline failures and data integration issues.\nOptimize pipelines for performance, scalability, reliability, and cost.\nDesign and implement modern Data Lake, Lakehouse, and Data Warehouse architectures.\nWork with Azure Data Lake Storage Gen2 and Microsoft OneLake.\nImplement Bronze, Silver, and Gold data layers.\nDesign dimensional data models using Star and Snowflake schemas.\nDevelop fact and dimension tables.\nImplement Slowly Changing Dimensions (SCD).\nWork with Delta Lake and related technologies.\nImplement partitioning and performance optimization strategies.\nSupport enterprise data warehouse modernization and migration initiatives.\nDevelop integrations between Azure services and enterprise applications.\nImplement secure and scalable cloud data architectures.\nSupport cloud migration and modernization initiatives.\nMonitor Azure resources and optimize platform performance and cost.\nApply cloud architecture and engineering best practices across data solutions.\nDevelop solutions using Fabric Lakehouse and Data Warehouse.\nBuild pipelines using Fabric Data Factory.\nDevelop Dataflows Gen2.\nWork with OneLake.\nDevelop Fabric notebooks using PySpark, Python, and Spark SQL.\nImplement Delta Lake-based data architectures.\nSupport Direct Lake and Power BI integration.\nManage Fabric workspaces and deployment processes.\nMonitor and optimize fabric capacity utilization.\nDevelop scalable data transformations using Python, PySpark, and Spark SQL.\nProcess large datasets using distributed computing.\n\nRequirements: \n6 to 10 years of relevant experience in Azure Data Engineering.\nMinimum 6 years of hands-on experience with Azure Data Engineering components, including PySpark, SQL, Azure Data Factory, and Azure Data Services.\nMinimum 2 years of experience with Azure Synapse Analytics or Microsoft Fabric.\nStrong experience in data engineering, data integration, data transformation, and enterprise data platforms.\nAbility to work independently with minimal supervision and contribute through hands-on development.\nExperience with pipeline migration using PySpark and SQL.\nExperience working with Azure technologies, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL Database, Azure SQL Managed Instance, Azure Functions, Azure Key Vault, Azure Event Hubs, Azure Storage, Microsoft Entra ID, and Microsoft Fabric.\n\nNice to Have: \nExperience across both Azure Synapse Analytics and Microsoft Fabric.\nExperience with Power BI integration and Direct Lake.\nSkills\nAzure, Azure Synapse, Fabric, Microsoft Azure, Microsoft Fabric, PySpark, Spark, 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