Data Engineer

prodigal llc; Bengaluru; On-site; INR 900,000 - 1,800,000; Full time

Benefits offered by this job

Health insurance for you and family

Meals at office

Travel reimbursement

Unlimited leaves

Gym membership

Learning & development

Flexible work schedule

Job summary

Prodigal is seeking a Data Engineer in Bengaluru to design and scale data pipelines within a Databricks data lake. You will transform raw data into reliable assets using SQL and modern tools, and collaborate with teams to generate insights for AI initiatives.

You will work in a fast-paced office in Koramangala, Bengaluru, using AWS services and a mix of Python/SQL. The role emphasizes data quality, performance, and practical ML data support.

Qualifications

• 1 year of professional experience in data engineering.
• Experience with SQL, NoSQL, and scripting languages (Python/R).
• Experience building and maintaining data pipelines using Airflow, SQL tasks, and stored procedures.
• Knowledge of data visualization tools like Tableau, Hex, or Power BI.
• Experience with AWS services (Lambda, S3, CloudFront, SQS, etc.).

Responsibilities

• Design, build, and manage robust data pipelines in our Databricks data lake.
• Transform raw data into clean, reliable assets using SQL and transformation tools like dbt.
• Collaborate with cross-functional teams to deliver actionable insights for products, AI, and decisions.
• Support AI/ML initiatives by validating model performance and data needs.

Skills

Data engineering

SQL

Python/R

NoSQL

Data pipelines

Databricks

Airflow

AWS

Tools

Airflow

Tableau

Hex

Power BI

MongoDB

PostgreSQL

Redis

Databricks

Lambda

S3

Job description

About Prodigal

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, we'd love to hear from you!

Responsibilities

• 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.

Requirements

• 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 (Koramangala,Bengaluru)

Our Tech Stack

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

What we offer

Top Tier Benefits

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 - https://www.prodigaltech.com/our-story

What shapes our thinking - https://link.prodigaltech.com/our-thesis

Our website - https://www.prodigaltech.com/