{"id":868460,"url":"https://alion.io/job/prodigal-data-engineer","title":"Data Engineer","company":{"id":687481,"name":"PRODIGAL","domain":"prodigal.com","url":"https://alion.io/company/prodigal-2","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"C","score":67,"open_postings":11,"ghost_share":0.545,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-29T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14000,"max_usd":33000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":9},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Claude","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon EC2","optional":true},{"name":"Amazon EKS","optional":true},{"name":"Kubernetes","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Redis","optional":true}],"status":"live","first_seen_at":"2026-09-03T03:12:03Z","employer_posted_date":"2026-09-10","last_verified_at":"2026-09-29T11:28:33Z","board_verified":true,"closed_at":null,"days_open":27,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":26},"description":"About Prodigal\nProdigal is the connected AI platform leading financial institutions use to run their operations.\nWe work with banks, lenders, credit unions, and other financial companies that lend money to people and manage those relationships over time.\nThese institutions make millions of high-stakes decisions every day. Who should they reach? When should they reach them? What should they say or offer? When should a case move to a human? How should that change based on the borrower, the account, previous interactions, and the regulations involved?\nGetting those decisions right requires a deep understanding of the people, processes, rules, and edge cases behind them.\nProdigal has spent the last eight years building that understanding. More than a billion interactions between financial institutions and their customers have shaped the intelligence, guardrails, and AI agents we now run in production across North America.\nToday, our AI agents analyze conversations, capture context, guide human agents, decide the next action, conduct customer conversations, orchestrate outreach, and help people complete payments and resolutions. They are connected, so what is learned in one interaction can inform what happens next.\nWe are expanding this swarm of AI agents across more of the work financial institutions do: originations, document processing, back-office workflows, servicing, and other critical operations where money, identity, people, and regulation intersect.\nWe are backed by Y Combinator, Accel, and Menlo Ventures, and work with 100+ financial institutions across North America. Listen directly from our CTO, Cofounder - Sangram Raje\n\nAbout the role - \nWe are looking for a passionate and driven Data Engineer to join our team. You will be instrumental in building scalable data pipelines, generating powerful insights, and supporting our AI/ML initiatives. If you enjoy working across data engineering and analytics and want to help shape the future of Agentic AI, we'd love to hear from you!\nResponsibilities\nDesign, build and manage robust data pipelines for collecting, transforming and modeling data within our Databricks data lake - dbt is your primary tool, not an afterthought\nOwn the dbt layer end to end - models, sources, tests, macros, incremental strategies and documentation. If it touches transformation, it goes through dbt and you're accountable for it being clean, tested and re-runnable\nTurn raw, messy data into reliable, well-modeled assets that downstream teams can actually trust - no untested models, no undocumented logic, no shortcuts\nCollaborate closely with cross-functional teams to deliver actionable insights that drive product, AI and business decisions - translating business logic into dbt models that are built to last\nSupport AI and ML initiatives by ensuring clean, validated and well-structured data is always available when the models need it\nIdentify and fix performance bottlenecks in dbt models, Databricks queries and downstream reporting pipelines\nRequirements \n2-3 years of hands-on experience in data engineering - you've built things in production, not just in notebooks\nStrong SQL - you can write and reason about complex joins, aggregations and window functions, and you know why a query is slow before you tune it\nPython for data engineering with production-grade PySpark or Spark SQL experience. Databricks strongly preferred\nDimensional modeling - star schemas, fact vs dimension grain, SCD Type 2, and incremental loads you can confidently re-run without breaking things\ndbt as your transformation framework of choice - models, tests, sources and incremental strategies are second nature to you\nAWS hands-on experience across Lambda, S3, CloudFront, SQS and beyond\nAI-native workflow - we ship with Claude Code and Cursor and we expect you to use them well, not just know they exist\nSharp problem solving - you find the right balance between getting it right and getting it done, and communicate clearly when tradeoffs are being made\nSelf-driven and curious - you thrive in fast paced environments, pick things up quickly and keep an eye on what's emerging in the data ecosystem\nBonus - Foundational knowledge in ML/AI fundamentals\nMode of Work - In-Office (Koramangala,Bengaluru)\nOur Tech Stack\nProducts built using Python, Cursor, Claude, dbt, Airflow\nDatabases such as MongoDB, PostgreSQL, Redis, Databricks, \nDeployments on EKS, EC2, Lambda and other AWS services\nWhat we offer\nTop Tier Benefits \nHealth insurance for you and your family, meals at office on us, travel reimbursement, unlimited leaves, subsidized gym membership, unlimited learning & development, flexible work schedule and a world-class team to learn and grow with! \nFrom day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US.\nTo learn more about us - please visit the following:\nOur Story - https://www.prodigaltech.com/our-story\nWhat shapes our thinking - https://link.prodigaltech.com/our-thesis\nOur website - https://www.prodigaltech.com/","description_format":"text","description_chars":5382,"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":["Flexible schedule","Gym membership","Health insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Services","Sports Organizations"],"lifecycle":[{"event":"open","at":"2026-09-13T15:26:26Z"}],"liveness":{"score":35,"band":"fade","label":"Fading","p_open":1,"p_active":0.461,"p_room":0.75,"age_days":26,"expected_fill_days":30,"reasons":["conf:7","stale_co","win:late","comp:junior"],"computed_at":"2026-09-29T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/prodigal-data-engineer","json_url":"https://alion.io/job/prodigal-data-engineer.json","meta":{"generated_at":"2026-09-30T03:32:59Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2539,"day_limit":5000,"remaining_today":2461,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}