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Job Description Databricks BI / AI BI Genie Specialist (AWS Cloud) Position: Senior Data & BI Engineer Location: [Hybrid] Experience: 610 years Domain: Data Engineering, Business Intelligence, Cloud Analytics Role Overview We are seeking a highly skilled Databricks BI Specialist with expertise in AI BI Genie (or similar BI/AI-driven visualization tools) to design, develop, and optimize business intelligence solutions on AWS cloud The role requires strong data modeling, performance tuning, and architectural knowledge of data engineering pipelines to deliver scalable and insightful analytics for business stakeholders, Key Responsibilities BI & Analytics Delivery Develop and manage BI dashboards and AI-driven insights using Databricks AI BI Genie (or equivalent BI/ML-powered analytics tools), Translate business requirements into technical BI solutions with strong storytelling and visualization, Design and optimize semantic layers, data marts, and curated datasets for BI consumption, Enable self-service BI & AI-driven insights for business users, Data Engineering & Modeling Collaborate with data engineers to design scalable data pipelines in Databricks on AWS, Define and implement star schema, snowflake, and data vault models for analytical workloads, Ensure data consistency, lineage, and governance via Unity Catalog (or equivalent metadata framework), Optimize query performance, indexing, caching, and compute resource allocation for BI workloads, Cloud & Architecture Design BI solutions aligned with AWS cloud architecture (S3, Redshift, Glue, EMR, Athena, ), Work closely with data architects to ensure scalability, reliability, and performance of BI systems, Ensure compliance with data security, privacy, and governance standards, Collaboration & Leadership Partner with Product Owners, Data Architects, and Business Analysts to define BI roadmap, Guide junior engineers in data modeling and BI development best practices, Contribute to performance benchmarking and architectural reviews for BI workloads, Required Skills & Experience 610 years of experience in BI & Data Engineering on cloud platforms, Strong expertise in Databricks (Delta Lake, SQL, PySpark) and BI tools (Databricks Genie, Tableau, Power BI, or Looker), Solid understanding of AWS cloud services (S3, Redshift, Glue, Lambda, Athena, EMR), Advanced knowledge of data modeling techniques (star schema, snowflake, normalized, data vault), Strong SQL optimization and performance tuning experience, Experience with architectural concepts in large-scale data platforms (batch + streaming), Familiarity with ML/AI-based BI features (, AI-driven insights, automated narrative generation), Excellent communication and stakeholder management skills, Nice to Have Experience with Unity Catalog or similar governance frameworks, Exposure to AI/ML model integration with BI tools, Knowledge of DevOps & CI/CD for BI pipelines (Terraform, GitHub Actions, Jenkins), Background in financial services, retail, or healthcare analytics (domain-specific BI), Education Bachelors or Masters in Computer Science, Data Engineering, Information Systems, or related field, Relevant certifications in AWS, Databricks, or BI tools are a plus, Experience 6-8 Years Skills Primary Skill: BI & Visualization Development Sub Skill(s): BI & Visualization Development Additional Skill(s): AWS CloudFormation, Power BI, AI/ML Development, BI & Visualization Development, databricks, CI/CD About The Company Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail & CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence We accelerate experience-led transformation in the delivery of digital platforms Infogain is also a Microsoft (NASDAQ: MSFT) Gold Partner and Azure Expert Managed Services Provider (MSP), Infogain, an Apax Funds portfolio company, has offices in California, Washington, Texas, the UK, the UAE, and Singapore, with delivery centers in Seattle, Houston, Austin, Krak?w, Noida, Gurgaon, Mumbai, Pune, and Bengaluru,
