{"id":2693481,"url":"https://alion.io/job/infosys-databricks-architect","title":"Databricks Architect","company":{"id":223,"name":"Infosys","domain":"infosys.com","url":"https://alion.io/company/infosys","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"A","score":95,"open_postings":245,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":93,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","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":30000,"max_usd":56000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":11,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Jenkins","optional":false},{"name":"pySpark","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Python","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-05T09:32:26Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-16T22:23:18Z","board_verified":true,"closed_at":null,"days_open":11,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":11},"description":"We are seeking an experienced Databricks, Snowflake and PySpark Architect to design, architect, and deliver scalable cloud-based data platforms and modern analytics solutions. The ideal candidate will have deep expertise in data architecture, cloud-native technologies, data engineering best practices, and large-scale data transformation programs. The role involves collaborating with business stakeholders, solution architects, and engineering teams to build high-performance, secure, and cost-efficient data ecosystems leveraging Databricks, Snowflake, and PySpark.\nResponsibilities\nDefine and drive enterprise-scale data architecture and modernization strategies.\nDesign end-to-end cloud data platforms using Databricks, Snowflake, and modern data engineering frameworks.\nArchitect scalable batch and real-time data processing pipelines for large datasets.\nLead data lake, lakehouse, and data warehouse implementations.\nProvide architectural guidance on performance optimization, scalability, governance, security, and reliability.\nWork closely with business stakeholders to understand analytical and reporting requirements.\nReview technical designs, conduct architecture assessments, and establish best practices.\nMentor data engineers and technical leads across project engagements.\nLead technology evaluations, proof-of-concepts (POCs), and solution accelerators.\nDrive cloud migration and modernization initiatives from legacy data platforms.\nEnsure adherence to enterprise security, compliance, and data governance standards.\nCollaborate with DevOps and platform teams to implement CI/CD and infrastructure automation for data solutions.\nTechnical requirements\n11+ years of experience in Data Engineering, Analytics, or Data Platform Architecture.\nStrong expertise in Databricks Lakehouse Platform.\nExtensive hands-on experience with Snowflake Data Cloud.\nExpert-level proficiency in PySpark and distributed data processing.\nStrong experience in designing enterprise-scale data lakes, data warehouses, and lakehouse architectures.\nHands-on experience with cloud platforms such as:\nAzure (ADF, ADLS Gen2, Synapse, Azure Databricks)\nAWS (S3, Glue, EMR, Redshift)\nGCP (BigQuery, DataProc, Cloud Storage)\nStrong SQL and data modeling skills (Dimensional Modeling, Data Vault, Star Schema).\nExperience building ETL/ELT frameworks and reusable data engineering accelerators.\nKnowledge of Data Governance, Metadata Management, Data Lineage, and Data Quality frameworks.\nExperience with orchestration tools such as Airflow, Azure Data Factory, or similar.\nExpertise in performance tuning and cost optimization within Databricks and Snowflake environments.\nExperience implementing CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or similar tools.\nAdditional responsibilities\nEnterprise Data Architecture\nSolution Design & Governance\nTechnology Strategy & Roadmap\nPresales & Client Advisory\nArchitecture Reviews\nData Platform Modernization\nTechnical Leadership & Mentoring\nCost Optimization & Non-Functional Requirements\nStakeholder Engagement\nPreferred skills\nTechnology->Data Engineering->Databricks\nEducation\nBachelor of 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