Data Engineer

Prodigal is the connected AI platform leading financial institutions use to run their operations.

We work with banks lenders credit unions and other financial companies that lend money to people and manage those relationships over time.

These 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

Getting those decisions right requires a deep understanding of the people processes rules and edge cases behind them.

Prodigal 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.

Today 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.

We 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.

We are backed by Y Combinator Accel and Menlo Ventures and work with 100 financial institutions across North America.

About the role -

We are looking for a passionate and drivenData 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 wed love to hear from you!

• Design build and manage robust data pipelines for collecting transforming and modeling data effectively within our Databricks data lake.
• Turn raw data into clean reliable and tested assets using SQL and modern transformation tools like dbt.
• Collaborate closely with cross-functional teams to deliver actionable insights that drive strategic products AI and business decisions.
• Contribute to AI research initiatives by validating model performance and supporting data needs for machine learning projects.
• Identify and address performance bottlenecks in data processing analytics and reporting.

• 1 year of professional experience in data engineering
• Working with data querying and scripting languages (e.g. SQL NoSQL Python/R)
• Experience building and maintaining data pipeline processes using tools like Airflow SQL tasks and stored procedures.
• Working knowledge of data visualization tools like Tableau Hex or Power BI.
• Experience working with AWS services such as Lambda S3 Cloudfront SQS and more
• Good problem solving critical thinking and communication skills. Should be able to find the right balance between perfection and speed of execution
• Self-starter and self-learner who is comfortable working in a fast paced environment while continuously evaluating emerging technologies
• Bonus: Foundational knowledge in fundamentals of Machine Learning and Artificial Intelligence

Mode of Work - In-Office (KoramangalaBengaluru)

• Products built using Python Devin Cursor
• Databases such as MongoDB PostgreSQL Redis Databricks
• Deployments on EKS EC2 Lambda and other AWS services

Health 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!

From 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.

To learn more about us - please visit the following:

Our Story - shapes our thinking - website - Experience:

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