{"id":2034757,"url":"https://alion.io/job/weekday-resident-solution-architect-rsa-data-databricks","title":"Resident Solution Architect (RSA) - Data & Databricks","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":107,"ghost_share":0,"stale_share":0.972,"repost_share":0,"time_to_fill_p50_days":5,"computed_at":"2026-10-14T06:34:16Z"}},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":32000,"max_usd":56000,"period":"year","method":"role_seniority_country_cell","sample_n":34},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"MLFlow","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-07T15:33:43Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-14T03:37:58Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"'\n: - ( - )\nExperience: 8+ yrs\nLocation: Remote (India)\nJob Type: Full-time\nWe are looking for an experienced Resident Solution Architect (RSA) - Data & Databricks to lead the design and delivery of scalable, cloud-based data and analytics solutions for enterprise customers. The role requires strong expertise in Databricks, Data Engineering, PySpark, Python, SQL, Lakehouse Architecture, and Cloud platforms.\nThe ideal candidate will combine deep technical expertise with strong customer-facing and consulting capabilities. You will work closely with enterprise stakeholders to understand complex business and technology requirements, design effective data solutions, lead architecture discussions and POCs, and provide technical direction to engineering teams.\nRequirements\nKey Responsibilities\nDesign end-to-end Data, Analytics, and Lakehouse solutions using Databricks.\nDevelop and review scalable ETL/ELT pipelines and enterprise data platforms.\nWork hands-on with Databricks, Apache Spark, PySpark, Python, and SQL.\nDesign solutions using Delta Lake, Unity Catalog, Databricks SQL, and Databricks Workflows.\nDevelop scalable data architectures across Azure, AWS, and GCP environments.\nConduct technical discovery sessions, architecture workshops, and solution discussions with enterprise customers.\nUnderstand business and technical requirements and translate them into scalable architecture and implementation approaches.\nPrepare High-Level Designs (HLD), Low-Level Designs (LLD), architecture diagrams, technical proposals, and solution documentation.\nLead POCs, technical demonstrations, solution validations, and architecture assessments.\nProvide technical guidance, mentoring, and architectural direction to Data Engineering teams.\nReview data pipelines, architecture designs, code, and implementation approaches for scalability and maintainability.\nTroubleshoot and optimise Databricks and Spark workloads for performance, scalability, reliability, and cost efficiency.\nSupport data platform modernisation, migration, and transformation initiatives.\nCollaborate with Sales, Pre-Sales, Delivery, Product, and Engineering teams on technical solutioning.\nEngage with senior customer stakeholders to communicate architecture decisions, technical recommendations, risks, and trade-offs.\nIdentify opportunities to improve data platform architecture, engineering practices, automation, and operational efficiency.\nStay current with developments across Databricks, cloud data platforms, distributed computing, and modern data engineering technologies.\nWhat Makes You a Great Fit\n8+ years of experience in Data Engineering, Data Architecture, Solution Architecture, Big Data, or a closely related field.\nStrong hands-on expertise in Databricks and enterprise data platforms.\nStrong knowledge of Apache Spark and PySpark.\nAdvanced programming skills in Python and SQL.\nStrong understanding of Lakehouse Architecture, Delta Lake, Unity Catalog, Databricks SQL, and Databricks Workflows.\nProven experience designing scalable ETL/ELT pipelines, data platforms, data models, and data warehouses.\nExperience working with at least one major cloud platform: Azure, AWS, or GCP.\nStrong understanding of distributed data processing, scalability, reliability, and data platform architecture.\nHands-on experience with performance tuning and optimisation of Databricks and Spark workloads.\nProven experience in technical solution design, architecture workshops, POCs, technical demonstrations, and solution validation.\nStrong customer-facing consulting experience with the ability to engage Architects, CTOs, CDOs, Engineering Managers, and senior technology stakeholders.\nExcellent communication, presentation, stakeholder-management, and technical storytelling skills.\nAbility to provide technical leadership and mentorship to Data Engineering teams.\nStrong analytical and problem-solving skills with a structured approach to complex technical challenges.\nExperience with Databricks certification would be an advantage.\nExposure to Snowflake, Kafka, Spark Streaming, dbt, Terraform, CI/CD, MLflow, MLOps, GenAI, LLM/RAG, or data migration is desirable.\nStrong ownership mindset with the ability to work independently in a remote, customer-facing 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