{"id":3299772,"url":"https://alion.io/job/axtria-senior-associate","title":"Senior Associate","company":{"id":63203,"name":"Axtria","domain":"axtria.com","url":"https://alion.io/company/axtria","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18000,"max_usd":39000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Cortex","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Informatica","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Sentiment Analysis","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Looker","optional":true},{"name":"Power BI","optional":true},{"name":"Prometheus","optional":true},{"name":"RAG","optional":true},{"name":"Tableau","optional":true}],"status":"live","first_seen_at":"2026-10-26T22:09:43Z","employer_posted_date":null,"last_verified_at":"2026-10-26T22:09:43Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"Job Title: Snowflake Developer (Data Lake Program with Snowflake Cortex)\n\nRole Overview\n\nThe Snowflake Developer is responsible for building and optimizing data pipelines and analytical datasets within a Snowflake-based data lakehouse. This role also includes leveraging Snowflake Cortex to enable AI-driven data transformations, natural language processing, and intelligent data applications directly within the data platform.\n\nKey Responsibilities\n\n Data Ingestion & Integration\nDevelop and maintain scalable data ingestion pipelines (batch and near real-time).\nLoad data from databases, APIs, files, and streaming systems into Snowflake.\nHandle structured and semi-structured data (JSON, Parquet, Avro, CSV).\nIntegrate Snowflake with cloud storage platforms (S3, Azure Data Lake, GCS).\n Data Transformation (ELT)\nBuild ELT pipelines using Snowflake SQL and native features (Streams, Tasks, Dynamic Tables).\nImplement transformations across Bronze, Silver, and Gold layers.\nUse tools like dbt for modular, reusable, and testable transformations.\n Snowflake Cortex & AI Enablement\nLeverage Snowflake Cortex functions within SQL for AI-powered transformations.\nImplement use cases such as:\nText summarization of large datasets (logs, documents)\nSentiment analysis and classification\nNatural language enrichment of datasets\nWork with vector embeddings and similarity search for semantic use cases.\nAssist in building AI-ready datasets for downstream analytics and ML.\nCollaborate with data scientists to integrate AI/ML logic into Snowflake pipelines.\nSupport simple prompt engineering within Cortex functions for optimized outputs.\n Data Modeling\nDesign and implement analytical data models (star schema, snowflake schema).\nBuild fact and dimension tables optimized for BI and AI use cases.\nEnsure datasets are structured for both analytics and AI consumption.\n Performance & Cost Optimization\nOptimize SQL queries and Snowflake workloads.\nUse clustering, caching, and efficient compute strategies.\nMonitor warehouse usage and control costs, including Cortex consumption.\n Data Quality & Validation\nImplement data validation checks and quality frameworks.\nEnsure accuracy, completeness, and consistency of data.\nDebug and resolve pipeline and data issues.\n Security & Governance\nApply RBAC, masking policies, and row-level security.\nEnsure compliance with data governance and privacy standards.\nMaintain proper documentation and lineage for datasets.\n Collaboration & Agile Delivery\nWork with architects, analysts, and AI/ML teams.\nTranslate business and AI use cases into technical implementations.\nParticipate in Agile development processes.\n\nRequired Skills & Qualifications\n\nCore Snowflake Skills\n\nStrong hands-on experience with Snowflake.\nAdvanced SQL skills with performance tuning.\nExperience with Snowflake features:\nStreams, Tasks, Dynamic Tables\nTime Travel, Zero-Copy Cloning\n\nSnowflake Cortex & AI Skills\n\nBasic to intermediate experience with Snowflake Cortex functions.\nUnderstanding of:\nGenerative AI concepts (LLMs, embeddings)\nText processing and NLP basics\nFamiliarity with:\nPrompt engineering techniques\nSemantic search and vector similarity concepts\n\nData Engineering Skills\n\nExperience with ELT/ETL tools (dbt, Airflow, Informatica).\nKnowledge of cloud platforms (AWS / Azure / GCP).\nFamiliarity with data lake/lakehouse architecture.\n\nProgramming & Tools\n\nProficiency in SQL and working knowledge of Python.\nExperience with Git and CI/CD pipelines.\n\nSoft Skills\n\nStrong analytical and problem-solving abilities.\nGood communication and collaboration skills.\nWillingness to learn and adapt to AI-driven data technologies.\n\nPreferred Qualifications\n\nSnowflake certification (SnowPro Core).\nExperience working on AI-enabled data platforms.\nExposure to vector databases or RAG architectures.\nFamiliarity with BI tools (Power BI, Tableau, Looker).\nUnderstanding of DataOps / MLOps practices.\n\nKey Deliverables\n\nScalable and reliable data pipelines.\nAI-enriched datasets using Snowflake Cortex.\nOptimized queries and cost-efficient workloads.\nHigh-quality, analytics- and AI-ready data models.\n\nSuccess Metrics\n\nPipeline reliability and performance.\nAdoption of AI-powered data transformations.\nQuery efficiency and cost optimization (including Cortex usage).\nData quality and stakeholder satisfaction.","description_format":"text","description_chars":4318,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Predictive Analytics","Management Consulting","Healthcare & Life Sciences Consulting","Analytics & BI Consulting"],"lifecycle":[{"event":"open","at":"2026-10-26T23:09:45Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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