Senior Data Engineer

About Us

Rho is the modern banking platform built for the AI era. Startups and growth-stage companies can open accounts in minutes, issue cards, manage expenses, pay bills, and close the books – all in one connected platform backed by real human support.

About the Role

Our team is looking for a Senior Data Engineer to join our data products team and help build & scale Rho's commercial banking technology.

The Data team builds data products for internal stakeholders and customers directly, maintaining a strong data driven culture across the company. This means treating data, pipelines, and ML systems as products in their own right: owned, versioned, documented, and built for other teams to discover and consume, not just infrastructure that sits behind the scenes. A key part of this role is building horizontal data products: reusable, ML-powered systems like an internal OCR pipeline, a transaction coding suggestion engine, and RAG-based and agentic systems that leverage our data to automate and augment internal workflows, that serve multiple teams and use cases across the company.

Technologies we use for data: Python, Go, Snowflake, DBT, PostgreSQL, Kubernetes, Terraform, Prometheus, Google Cloud Services, Omni, Hex

The ideal candidate is a strong software and data engineer with good taste & judgement, someone who knows what good looks like, and subscribes to a “strong opinions, weakly held” mindset.

Responsibilities:

- Design, build, and own data products, reliable, scalable, well-documented pipelines and datasets that other teams can discover, trust, and build on directly

- Apply strong software engineering practices (clean code, testing, version control, CI/CD) to data products and ML systems, treating them with the same rigor as production software, while moving fast in AI-first world

- Build horizontal, ML-driven data products, such as our OCR pipeline for document processing, our transaction coding suggestion system, and RAG/agentic tools, designed to be reused across multiple teams rather than built for a single use case

- Define and uphold data product quality: implement quality checks, monitoring, alerts, and SLAs so consumers of a data product can rely on it the way they'd rely on any well-run internal API

- Partner directly with the stakeholders who consume your data products to understand their needs, gather feedback, and iterate, treating them as customers rather than downstream requesters

- Collaborate with business intelligence and analytics teams to turn business needs into data products that are easy to find, understand, and self-serve from

- Lead initiatives to grow Rho's catalog of data products and improve the platform that supports them, expanding what other teams can build on top of

Requirements:

- 5+ years of experience in data engineering, software engineering, or DevOps

- Proficiency in workflow orchestrators such as Airflow, Dagster, or Prefect

- Experience with major data platforms including Snowflake, Databricks, BigQuery, or in-house HDFS-based solutions

- Skilled at building data infrastructure using GCP, AWS, or comparable cloud providers

- Comfortable managing and deploying services on Kubernetes

- Practical experience with Terraform or Pulumi for automating infrastructure

- Advanced programming abilities in Python and Go are integral to this role, along with strong SQL skills (Java experience also considered)

- Proven experience building, owning, and iterating on data products or data pipelines based on consumer feedback, not just building infrastructure in isolation

- Experience designing systems for reuse across multiple teams

- Good communication skills and a team-oriented, collaborative approach, comfortable working directly with the people who consume what you build

Nice To Haves:

- Experience building a data platform or data product suite from the ground up

- Experience integrating or deploying ML models into production systems (e.g., classification, suggestion, or extraction models)

- Experience with RAG (Retrieval-Augmented Generation) systems and vector databases

- Familiarity with ML infrastructure tooling such as MLflow

- Experience building or deploying agents

- Experience with data modeling and data product approaches such as Data Mesh, Kimball, Inmon, Data Vault, or similar

- Experience working with streaming data systems

- Familiarity with Prometheus or other time-series databases used for monitoring

- Experience with business intelligence (BI) tools such as Omni

What we offer

Our people are our most valuable asset. Base salary may vary depending on relevant experience, skills, geographic location, and business needs.

Benefits:

- Top-notch Private Healthcare Insurance for you and your family members

- Generous PTO policy

- Lunch at work

- Covered costs for parking for onsite staff

- Learning and development budget

- Paternity leave

- Hybrid work environment (with old town Belgrade office)