{"id":3039404,"url":"https://alion.io/job/exl-databricks-developer-data-architect","title":"Databricks Developer / Data Architect","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":80,"open_postings":252,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"hybrid","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":{"min_usd":27000,"max_usd":50000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Airflow","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"Delta Lake","optional":true},{"name":"Scrum","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-06-22T11:46:31Z","employer_posted_date":"2026-06-22","last_verified_at":"2026-10-24T08:38:00Z","board_verified":true,"closed_at":null,"days_open":123,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":123},"description":"Job Description: Databricks Developer / Data Architect\nPosition Title\nDatabricks Developer / Data Architect\nLocation\nHybrid/ Remote\nEmployment Type\nFull-Time / Contract\nJob Summary\nWe are seeking an experienced Databricks Developer / Data Architect to design, implement, and optimize modern data platforms and ETL pipelines using Databricks and cloud-native technologies. The ideal candidate will have strong expertise in data architecture, Lakehouse implementation, Medallion Architecture, and scalable ETL development across Azure and AWS environments.\nThe role involves setting up Databricks workspaces, configuring data integrations and Lakehouse Federation, building enterprise-grade ETL workflows, and enabling high-performance analytics solutions.\nKey Responsibilities\nData Architecture & Modeling\nDesign and implement scalable enterprise data architectures using Databricks Lakehouse platform \nConfigure and manage Databricks workspaces, clusters, access controls, and governance \nImplement Medallion Architecture (Bronze, Silver, Gold layers) for data processing and analytics \nSet up and manage Lakehouse Federation and data connectors for multi-source integration \nDevelop logical and physical data models for structured and semi-structured datasets \nEnsure data quality, security, scalability, and performance optimization \nETL Development\nDevelop and maintain scalable ETL/ELT pipelines using PySpark, Spark SQL, and Databricks workflows \nBuild reusable data ingestion frameworks for batch and streaming workloads \nOptimize Spark jobs for performance, cost efficiency, and reliability \nIntegrate data from relational and NoSQL databases, cloud platforms, and external systems \nAutomate deployment and monitoring of ETL workflows \nCloud & Platform Engineering\nWork with Azure and AWS cloud services to deploy and manage data solutions \nConfigure integrations with Snowflake, Postgres, MongoDB, DynamoDB, Cloudera, and Domino Server \nSupport CI/CD, infrastructure automation, and environment management \nCollaborate with cross-functional teams including Data Scientists, Analysts, and Business stakeholders \nRequired Skills & Qualifications\n5+ years of experience in Data Engineering / Data Architecture \nStrong hands-on experience with Databricks platform \nExpertise in:Python \nApache Spark \nPySpark \nSQL \n\nStrong understanding of:Lakehouse Architecture \nMedallion Architecture \nData Modeling \nETL/ELT Design Patterns \n\nExperience with cloud platforms:Microsoft Azure \nAWS \n\nExperience integrating with:PostgreSQL \nDynamoDB \nMongoDB \nSnowflake \nCloudera \nDomino Server \n\nKnowledge of performance tuning and optimization in Spark/Databricks \nExperience with version control and DevOps practices \nPreferred Qualifications\nDatabricks Certification(s) \nExperience with Delta Lake and Unity Catalog \nFamiliarity with streaming frameworks and real-time data processing \nKnowledge of data governance and security best practices \nExperience in Agile/Scrum delivery models \nTechnical Stack\nDatabricks \nPython \nSpark / PySpark \nSQL \nAzure \nAWS \nSnowflake \nPostgreSQL \nMongoDB \nDynamoDB \nCloudera \nDomino Server \nSoft Skills\nStrong analytical and problem-solving abilities \nExcellent communication and stakeholder management skills \nAbility to work independently and collaboratively in fast-paced environments \nStrong documentation and solution design capabilities \nNice-to-Have\nExperience with Terraform or Infrastructure as Code \nExposure to ML/data science platforms \nExperience with orchestration tools such as Airflow or Azure Data Factory \n Job Description: Databricks Developer / Data Architect\nPosition Title\nDatabricks Developer / Data Architect\nLocation\nHybrid/ Remote\nEmployment Type\nFull-Time / Contract\nJob Summary\nWe are seeking an experienced Databricks Developer / Data Architect to design, implement, and optimize modern data platforms and ETL pipelines using Databricks and cloud-native technologies. The ideal candidate will have strong expertise in data architecture, Lakehouse implementation, Medallion Architecture, and scalable ETL development across Azure and AWS environments.\nThe role involves setting up Databricks workspaces, configuring data integrations and Lakehouse Federation, building enterprise-grade ETL workflows, and enabling high-performance analytics solutions.\nKey Responsibilities\nData Architecture & Modeling\nDesign and implement scalable enterprise data architectures using Databricks Lakehouse platform \nConfigure and manage Databricks workspaces, clusters, access controls, and governance \nImplement Medallion Architecture (Bronze, Silver, Gold layers) for data processing and analytics \nSet up and manage Lakehouse Federation and data connectors for multi-source integration \nDevelop logical and physical data models for structured and semi-structured datasets \nEnsure data quality, security, scalability, and performance optimization \nETL Development\nDevelop and maintain scalable ETL/ELT pipelines using PySpark, Spark SQL, and Databricks workflows \nBuild reusable data ingestion frameworks for batch and streaming workloads \nOptimize Spark jobs for performance, cost efficiency, and reliability \nIntegrate data from relational and NoSQL databases, cloud platforms, and external systems \nAutomate deployment and monitoring of ETL workflows \nCloud & Platform Engineering\nWork with Azure and AWS cloud services to deploy and manage data solutions \nConfigure integrations with Snowflake, Postgres, MongoDB, DynamoDB, Cloudera, and Domino Server \nSupport CI/CD, infrastructure automation, and environment management \nCollaborate with cross-functional teams including Data Scientists, Analysts, and Business stakeholders \nRequired Skills & Qualifications\n5+ years of experience in Data Engineering / Data Architecture \nStrong hands-on experience with Databricks platform \nExpertise in:Python \nApache Spark \nPySpark \nSQL \n\nStrong understanding of:Lakehouse Architecture \nMedallion Architecture \nData Modeling \nETL/ELT Design Patterns \n\nExperience with cloud platforms:Microsoft Azure \nAWS \n\nExperience integrating with:PostgreSQL \nDynamoDB \nMongoDB \nSnowflake \nCloudera \nDomino Server \n\nKnowledge of performance tuning and optimization in Spark/Databricks \nExperience with version control and DevOps practices \nPreferred Qualifications\nDatabricks Certification(s) \nExperience with Delta Lake and Unity Catalog \nFamiliarity with streaming frameworks and real-time data processing \nKnowledge of data governance and security best practices \nExperience in Agile/Scrum delivery models \nTechnical Stack\nDatabricks \nPython \nSpark / PySpark \nSQL \nAzure \nAWS \nSnowflake \nPostgreSQL \nMongoDB \nDynamoDB \nCloudera \nDomino Server \nSoft Skills\nStrong analytical and problem-solving abilities \nExcellent communication and stakeholder management skills \nAbility to work independently and collaboratively in fast-paced 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