{"id":4230821,"url":"https://alion.io/job/adrosonic-senior-data-engineer-microsoft-fabric","title":"Senior Data Engineer - Microsoft Fabric","company":{"id":4529397,"name":"Adrosonic","domain":"adrosonic.com","url":"https://alion.io/company/adrosonic","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":"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":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Rest API","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Git","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-11-13T09:35:30Z","employer_posted_date":null,"last_verified_at":"2026-11-13T09:35:30Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"At ADROSONIC, we are looking for a highly skilled Senior Data Engineer - Microsoft Fabric with 5+ years of hands-on experience in designing, building, and optimizing modern data platforms. The ideal candidate will bring strong expertise in Microsoft Fabric, Azure data services, and advanced data modeling practices.\n\nThis role demands deep technical strength in data engineering along with mandatory data modeling expertise to design scalable, analytics-ready, and high-performing data solutions. The candidate should possess a collaborative mindset and work seamlessly with BI teams, architects, stakeholders, and clients to deliver enterprise-grade data platforms.\n\nYou will play a key role in building modern cloud-based data architectures, enabling seamless reporting in Power BI, and ensuring efficient, reliable, and optimized data pipelines across projects.\n\nRequirements:\n5+ years of hands-on experience in Data Engineering.\nStrong expertise in Microsoft Fabric ecosystem and Azure data services including Azure SQL Database, Azure SQL Managed Instance, Azure Synapse Analytics, Azure Data Lake Storage Gen2, and Azure Data Factory.\nMandatory strong experience in Data Modeling (conceptual, logical, physical) with solid knowledge of dimensional modeling (Star/Snowflake schema) and data warehousing principles.\nAdvanced proficiency in SQL, including performance optimization and complex transformations and experience with NoSQL databases.\nHands-on experience in designing ETL/ELT pipelines using Fabric, Azure Data Factory, or Azure Databricks, with working knowledge of PySpark/Spark.\nGood understanding of data governance fundamentals, data quality, metadata management, and exposure to compliance standards.\nStrong analytical, troubleshooting, and stakeholder collaboration skills, with experience working in Agile delivery environments and version-controlled setups.\nBachelor's/Master's degree in Computer Science, Data Science, Information Systems, or a related field.\n\nKey Responsibilities:\nDesign and implement scalable data solutions using Microsoft Fabric (Lakehouse, Data Warehouse, Data Factory, Notebooks).\nArchitect hybrid data solutions integrating Microsoft Fabric with Azure Synapse Analytics and Azure SQL Managed Instance.\nBuild and manage Medallion architecture (Bronze, Silver, Gold layers) within OneLake.\nIntegrate Microsoft Fabric with Azure services such as Azure Data Lake Storage Gen2 to build scalable, secure, and performance-optimized data frameworks.\nDevelop efficient ingestion, transformation, and loading pipelines.\nOptimize Fabric workloads for performance, scalability, and cost efficiency.\nImplement secure connectivity using Azure Private Endpoints and VNet integration where required.\nDesign conceptual, logical, and physical data models.\nImplement dimensional modeling techniques (Star Schema, Snowflake Schema).\nDevelop well-structured fact and dimension tables optimized for analytical workloads.\nEnsure data models are optimized for Power BI and enterprise reporting.\nMaintain consistency, scalability, and performance across evolving data models.\nDesign data models using different database schemas (Kimball, Star, Snowflake) for optimal data retrieval and storage.\nEnsure models are optimized for both transactional (OLTP) and analytical (OLAP) workloads, using best practices in database design.\nDevelop ETL/ELT pipelines using Fabric Data Factory, Azure Data Factory, and related Azure services.\nIntegrate structured and unstructured data from Azure SQL Database, Azure SQL Managed Instance, Azure Data Lake Gen2, REST APIs, and external sources.\nImplement transformation logic using SQL, PySpark, or Spark frameworks.\nLeverage Azure Databricks for advanced data processing where required.\nEnsure data validation, quality checks, and reliability within pipelines.\nImplement secure credential management using Azure Key Vault.\nWork closely with BI developers to design analytics-ready datasets.\nEnsure seamless integration between Microsoft Fabric and Power BI.\nSupport backend optimization to improve dashboard performance.\nAct as a technical bridge between Data Engineering and BI teams.\nCollaborate seamlessly with internal stakeholders and external clients.\nGather, analyze, and translate business requirements into scalable technical solutions.\nClearly communicate data architecture decisions, pipeline designs, and modeling approaches.\nParticipate in client workshops, technical discussions, and solution presentations.\nEnsure strong alignment between business objectives and delivered data solutions.\nMonitor data pipeline performance using Azure Monitor & Log Analytics and resolve bottlenecks proactively.\nOptimize query performance across Fabric Warehouse, Azure Synapse, and Azure SQL MI environments.\nImplement logging, monitoring, and alerting mechanisms.\nEnsure high availability, reliability, and timely delivery of data.\nContinuously improve scalability and maintainability of data platforms.\nFollow data engineering standards, naming conventions, and documentation practices.\nImplement version control and CI/CD processes for data pipelines.\nPromote reusable components and clean coding practices.\nEnsure adherence to security standards and basic data governance principles.\nContinuously monitor and optimize the performance of data models, making improvements to ensure efficiency and scalability.\nConduct regular audits to ensure that the data models remain aligned with the organization's evolving data strategy.\n\nPreferred Qualifications:\nMicrosoft certifications such as DP-700 (Microsoft Fabric Data Engineer Associate).\nMicrosoft Azure certifications (e.g., Azure Data Engineer Associate).\nDomain experience in Insurance and Financial Services is a strong plus.\nExperience in client-facing or consulting environments.\nExposure to DevOps practices and Git-based version control.\nExperience handling enterprise-scale data environments.\n\nSoft Skills:\nStrong collaborative mindset.\nSeamless coordination with BI teams and stakeholders.\nStrong client communication and stakeholder management skills.\nOwnership-driven and proactive approach.\nStrong analytical and problem-solving abilities.\nAbility to work effectively in fast-paced, evolving environments.\nSkills\nAzure, Databricks, ELT, ETL, Lakehouse, Microsoft Fabric, Modeling, PySpark, SQL, Synapse, 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