{"id":3667645,"url":"https://alion.io/job/scryai-data-engineer","title":"Data Engineer","company":{"id":38400,"name":"Scryai","domain":"scryai.com","url":"https://alion.io/company/scryai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"C","score":56,"open_postings":19,"ghost_share":0.737,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Delhi, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"GCP","optional":true},{"name":"Google BigQuery","optional":true},{"name":"pySpark","optional":true},{"name":"RAG","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-03T06:33:36Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T12:45:58Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":1},"description":"SCRY AI is an innovative AI-driven technology company focused on building intelligent, scalable, and high-performance solutions. We work with modern technologies across Software Engineering, AI/ML, and Data to solve real-world business problems and deliver impactful digital products.\nRole Overview\nWe are looking for a skilled Data Engineer with 2-3 years of experience in building scalable data pipelines, backend services, and data processing systems. The ideal candidate should have strong hands-on experience in Python, SQL, ETL/ELT, API development, and database technologies, with exposure to AI/ML applications, Agentic AI, and cloud or on-premises deployments.\nKey Responsibilities\nDesign, develop, and maintain scalable ETL/ELT pipelines for processing structured and unstructured data.\nBuild data ingestion and transformation workflows using Python, SQL, and relevant data engineering frameworks.\nExtract, clean, validate, normalize, and transform data from APIs, databases, files, and other sources.\nDesign and optimize database schemas, data models, SQL queries, joins, indexes, and aggregations.\nWork with relational databases such as PostgreSQL/MySQL and NoSQL databases where required.\nDevelop batch and incremental data processing pipelines with appropriate error handling and recovery mechanisms.\nImplement data quality checks, validation rules, deduplication, and reconciliation to ensure data accuracy and consistency.\nIntegrate data pipelines and AI applications with SQL/NoSQL databases, APIs, enterprise systems, and customer-specific data sources.\nDevelop Agentic AI and workflow automation solutions using frameworks such as LangChain/LlamaIndex, including tool calling and external system integrations.\nBuild and optimize backend services and APIs to support data processing, AI/ML workflows, and enterprise integrations.\nWork directly with customers and stakeholders to understand requirements, troubleshoot issues, demonstrate solutions, and translate business needs into technical implementations.\nTake AI/ML solutions from POC to production, focusing on scalability, reliability, latency, monitoring, and maintainability.\nDeploy and troubleshoot data and AI applications using Docker across cloud, on-premises, and customer environments.\nImplement logging, monitoring, alerting, and performance optimization for data pipelines and production applications.\nFollow engineering best practices using Git, CI/CD, automated testing, and documentation, collaborating with Data Scientists, ML Engineers, Backend Engineers, and business teams.\nKey Qualifications\n2-3 years of experience in Data Engineering, Backend Engineering, ETL development, or a related role.\nStrong proficiency in Python and SQL, including complex queries, joins, CTEs, window functions, and query optimization.\nHands-on experience building ETL/ELT pipelines, data ingestion workflows, and transformation processes.\nExperience with relational databases, preferably PostgreSQL/MySQL, and database design principles.\nUnderstanding of data warehousing, dimensional modeling, indexing, partitioning, and incremental data processing.\nExperience integrating REST APIs, databases, CSV/Excel files, JSON, and other data sources.\nStrong experience with FastAPI/Flask, microservices, Docker, and backend architecture; Kubernetes is a plus.\nExperience with AWS/Azure/GCP and cloud or on-premises deployments.\nKnowledge of CI/CD, automated testing, Git, logging, monitoring, production debugging, and AI/ML inference optimization.\nExposure to LLMs, Agentic AI, tool calling, workflow automation, and frameworks such as LangChain/LlamaIndex.\nStrong problem-solving, communication, customer-facing, and collaboration skills, with the ability to work independently in fast-paced environments.\nGood to Have\nExperience with Apache Spark/PySpark, Kafka, or similar distributed data processing and messaging technologies.\nExposure to cloud data platforms and warehouses such as BigQuery, Redshift, or Azure Data Factory.\nExperience preparing datasets for AI/ML, GenAI, RAG applications, vector databases, or analytics pipelines","description_format":"text","description_chars":4102,"description_truncated":false,"requirements":{"experience_years_min":2,"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":["AI Consulting & Integration","Document AI"],"lifecycle":[{"event":"open","at":"2026-11-03T07:31:15Z"}],"visa":[],"liveness":{"score":60,"band":"ok","label":"Likely open","p_open":1,"p_active":0.602,"p_room":1,"age_days":1,"expected_fill_days":28,"reasons":["conf:3","stale_co","win:early","comp:junior"],"computed_at":"2026-11-04T06:34:25Z"},"pay":null,"html_url":"https://alion.io/job/scryai-data-engineer","json_url":"https://alion.io/job/scryai-data-engineer.json","meta":{"generated_at":"2026-11-04T15:06:32Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":22905,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-05T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":38400},"rest":"https://alion.io/mcp/rest/get_company?id=38400"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fscryai-data-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fscryai-data-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fscryai-data-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/scryai-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fscryai-data-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3667645}},{"tool":"search_jobs","arguments":{"company":"scryai.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3667645},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); 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