{"id":2337953,"url":"https://alion.io/job/ns-global-corporation-solution-architect","title":"Solution Architect","company":{"id":3800107,"name":"NS Global Corporation","domain":"nsglobalcorporation.com","url":"https://alion.io/company/ns-global-corporation","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":29000,"max_usd":50000,"period":"year","method":"role_seniority_country_cell","sample_n":34},"experience_years_min":7,"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":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"LLM","optional":true},{"name":"pySpark","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-12T09:52:46Z","employer_posted_date":null,"last_verified_at":"2026-10-12T09:52:46Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Position Overview : \n\nWe are seeking an experienced Databricks Data Science Solution Architect to provide technical leadership and hands-on development support to an established Data Science team. The ideal candidate will have strong Python development expertise and proven experience designing, developing, deploying, and operationalizing production-ready Data Science and Machine Learning solutions on Databricks.\n\nKey Responsibilities : \n\n- Design and architect scalable Data Science, Machine Learning, AI, and advanced analytics solutions using Databricks.\n\n- Develop and review production-quality Python code for Machine Learning models and Data Science applications.\n\n- Build and deploy solutions using Databricks Apps, Jobs, Workflows, Pipelines, MLflow, Unity Catalog, and Model Serving Endpoints.\n\n- Convert experimental notebooks and Machine Learning models into scalable, maintainable production applications.\n\n- Implement MLOps/ModelOps practices, including model versioning, experiment tracking, automated testing, CI/CD, deployment, monitoring, and retraining.\n\n- Optimize application performance, scalability, reliability, and cost.\n\n- Mentor Data Scientists and establish coding standards, reusable frameworks, and development best practices.\n\n- Collaborate with Data Engineering, Platform Engineering, ModelOps, and business teams.\n\n- Troubleshoot production issues and ensure solutions meet enterprise security and governance standards.\n\nRequired Skills and Experience : \n\n- 7+ years of experience in Data Science.\n\n- 5+ years of experience with Databricks products.\n\n- Strong hands-on Python development experience.\n\n- Proven experience building and deploying Data Science and Machine Learning solutions on Databricks.\n\n- Hands-on experience with Databricks Apps, Jobs/Workflows, Pipelines, MLflow, Unity Catalog, and Model Serving Endpoints.\n\n- Strong understanding of Machine Learning workflows, MLOps/ModelOps, and production model deployment.\n\n- Experience with Git, CI/CD, APIs, software engineering best practices, and cloud platforms such as AWS, Azure, or GCP.\n\n- Strong technical leadership, mentoring, troubleshooting, and communication skills.\n\nPreferred Skills : \n\n- Databricks certification.\n\n- Experience with PySpark, Spark, R, Posit Workbench, or Posit Connect.\n\n- Knowledge of Generative AI, LLM-based applications, model monitoring, and observability.\n\n- Experience in insurance, financial services, risk, or other regulated industries.\n\nIdeal Candidate Profile : \n\nWe are looking for candidates with hands-on experience building Python-based Data Science and Machine Learning solutions within Databricks, rather than profiles focused primarily on Data Engineering. 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