{"id":3647727,"url":"https://alion.io/job/softedge-consulting-databricks-ai-power-bi-reporting-developer","title":"Databricks AI & Power BI Reporting Developer","company":{"id":1381567,"name":"SoftEdge Consulting","domain":"softedge.ca","url":"https://alion.io/company/softedge","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Delhi, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Git","optional":true},{"name":"Machine Learning","optional":true},{"name":"Tableau","optional":true}],"status":"live","first_seen_at":"2026-11-02T21:20:28Z","employer_posted_date":null,"last_verified_at":"2026-11-02T21:20:28Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"Databricks AI & Power BI Reporting Developer\nExperience: 4–7 Years\nPrimary Skills\nDatabricks, AI/Analytics Reporting, Power BI, SQL, Python, PySpark, AWS\nRole Overview\nThe Data Engineer – Databricks AI & Power BI Reporting Developer will be responsible for designing, developing, and maintaining data solutions, analytical reporting, and AI-enabled insights using Databricks, Power BI, and AWS. The ideal candidate should have 4–7 years of relevant experience in data engineering, Databricks-based analytics and reporting, and Power BI report development. The candidate must have strong hands-on experience in developing interactive Power BI dashboards, transforming and analyzing data in Databricks, and building scalable data pipelines to support business intelligence and AI-driven reporting requirements. The role involves close collaboration with business stakeholders, data engineers, data architects, analytics teams, and implementation partners to deliver reliable, high-quality, and performance-optimized reporting solutions.\nKey Responsibilities\nDesign, develop, and maintain interactive Power BI reports, dashboards, and visualizations to meet business and analytical requirements.\nDevelop and optimize Databricks notebooks, SQL queries, and data transformation workflows using Python, PySpark, and Spark SQL.\nBuild and maintain data pipelines using AWS and Databricks to support reporting, analytics, and AI-related use cases.\nPrepare, transform, validate, and integrate data from multiple source systems for reporting and analysis.\nImplement and maintain Bronze, Silver, and Gold data layers using Databricks and Delta Lake.\nDevelop efficient data models, relationships, measures, and calculated columns using Power BI and DAX.\nConnect Power BI to Databricks and other data sources to deliver accurate, reliable, and timely business insights.\nWork with AI/ML-enabled analytics and reporting capabilities in Databricks to support predictive insights and advanced analytics, where required.\nPerform data profiling, reconciliation, validation, and troubleshooting to ensure report accuracy and data quality.\nOptimize Power BI dashboards, DAX calculations, data models, SQL queries, and Databricks workloads for performance and scalability.\nImplement data refresh schedules, incremental refresh, and appropriate reporting security, including row-level security where required.\nSupport data governance, metadata, lineage, and access management activities using Databricks Unity Catalog and related tools.\nCollaborate with business stakeholders to gather reporting requirements, translate business needs into technical solutions, and validate report outputs.\nParticipate in code reviews, testing, deployment, CI/CD, and production support.\nPrepare technical documentation and provide knowledge transfer to internal teams.\nRequired Skills\n4–7 years of relevant experience in Databricks analytics/reporting, Power BI development, data engineering, or a closely related role.\nStrong hands-on experience developing Power BI reports and dashboards.\nStrong knowledge of Power BI data modeling, DAX, Power Query, and report performance optimization.\nHands-on experience with Databricks notebooks, Databricks SQL, and data transformation.\nStrong SQL skills for data extraction, transformation, analysis, and validation.\nExperience with Python, PySpark, and Apache Spark.\nExperience integrating Power BI with Databricks and other enterprise data sources.\nUnderstanding of ETL/ELT processes, data pipelines, data quality, and data reconciliation.\nWorking knowledge of AWS cloud services and cloud-based data platforms.\nStrong analytical, troubleshooting, communication, and stakeholder collaboration skills.\nPreferred Skills\nExperience with Databricks AI capabilities and AI-assisted analytics or reporting.\nKnowledge of Databricks Mosaic AI, AI/BI capabilities, or machine learning integration for analytics use cases.\nExperience with Delta Lake, Unity Catalog, and Lakehouse architecture.\nExperience with AWS services used in data engineering and analytics.\nKnowledge of Tableau or other BI and visualization platforms.\nExperience with Git, CI/CD pipelines, and DevOps practices.\nUnderstanding of data governance, metadata management, data lineage, and security.\nDatabricks or Microsoft Power BI certifications.\nIdeal Candidate Profile\nThe ideal candidate will combine strong Databricks data and analytics expertise with hands-on Power BI report development skills. 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