{"id":1232546,"url":"https://alion.io/job/movate-solution-architect-data-analytics","title":"Solution Architect - Data & Analytics","company":{"id":2278,"name":"Movate","domain":"movate.com","url":"https://alion.io/company/movate","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":31000,"max_usd":55000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":33},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"pySpark","optional":true},{"name":"Python","optional":true},{"name":"Spark","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-08-19T07:29:55Z","employer_posted_date":null,"last_verified_at":"2026-08-19T07:29:55Z","board_verified":false,"closed_at":null,"days_open":59,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":59},"description":"Job Summary:\n\nWe are looking for an experienced Solution Architect to design and deliver scalable, secure, and future-ready Data & Analytics platforms on Azure. The role will focus on architecting enterprise-grade data solutions supporting reporting, analytics, AI/ML, and GenAI initiatives while ensuring compliance, governance, performance, and cost optimization.\n\nKey Responsibilities:\n\n- Design scalable, secure, and high-performance data platform solutions.\n\n- Architect data ingestion, transformation, storage, governance, and consumption layers.\n\n- Review functional and non-functional design documents and ensure alignment with enterprise standards.\n\n- Collaborate with business, engineering, security, enterprise architecture, and platform teams.\n\n- Ensure data solutions comply with architecture, cybersecurity, regulatory, and governance requirements.\n\n- Drive Databricks vendor engagements and Unity Catalog adoption across projects.\n\n- Support AI/ML, MLOps, RAG, and GenAI architecture use cases on enterprise data platforms.\n\n- Identify technical risks, resolve challenges, and support timely delivery of project milestones.\n\n- Optimize platform performance and cloud cost through continuous improvement.\n\nMandatory Skills:\n\n- Azure Data Lake / ADLS Gen2\n\n- Databricks and Unity Catalog\n\n- Data Architecture and Data Modeling\n\n- Data Integration and Enterprise Data Platform Design\n\n- SQL for analysis, validation, modeling, and performance optimization\n\n- Data Security, Governance, Metadata Management, and Lineage\n\nPreferred Skills:\n\n- Python and PySpark\n\n- Azure Synapse and Cloud-Native Architecture\n\n- AI/ML Lifecycle and MLOps\n\n- RAG and GenAI Solution Design\n\n- Terraform / Infrastructure as Code\n\n- Agile, DevOps, Cost Optimization, and Stakeholder Management\n\nRequired Experience:\n\n- 10+ years of overall experience preferred, with a strong background in data architecture and engineering.\n\n- Proven experience designing and implementing large-scale Azure-based data platforms.\n\n- Strong expertise in Azure Data Lake, Databricks, SQL, data modeling, and integration patterns.\n\n- Experience with metadata management, data governance, secure data access, and architecture governance.\n\n- Ability to translate business requirements into robust, scalable, and cost-effective technical solutions.\n\n- Strong communication skills with experience working with senior business and technology stakeholders.\n\nGood to Have:\n\n- Hands-on experience with AI/ML solution architecture and model lifecycle awareness.\n\n- Knowledge of MLOps, model deployment, monitoring, and operational governance.\n\n- Exposure to RAG, GenAI, Terraform, ARM templates, Python, PySpark, Synapse, Agile, and DevOps\nSkills\nSolution Architect, Solution Design, Artificial Intelligence, Transformation, Data 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