Build and maintain the pipelines and transformations behind those metrics, including dimensional modeling, ETL design, and the documentation and data dictionaries that make them usable by others
Contribute to the platform’s application and service layer — the interfaces, services and deployments through which partners consume the platform’s output
Investigate discrepancies and anomalies to root cause, and turn each finding into a durable check rather than a one-off fix
Use AI agents as a primary working method — to model and reverse-engineer data semantics, to implement and ship production code, and to design the agent workflows the platform itself runs on
Validate what AI produces: define the acceptance criteria, evaluation, and review that make agent-generated work safe to ship, and apply domain judgment where correctness cannot be automated
Build alerting and observability so that issues reach a named owner with enough context to act, and so the platform’s own health is visible
Work with partner teams to understand requirements and ensure data solutions align with Remitly’s goals
Communicate complex data findings and technical information to non-technical partners in Accounting, Treasury, Finance and Compliance, both verbally and through data visualizations
Identify ways to improve the reliability, efficiency and quality of the platform, so coverage grows faster than the effort required to operate it
Job Qualifications
5+ years as an analytics engineer or equivalent
Expert in SQL, git, and a programming language (Python, Scala, Java, or similar)
Experience in dimensional data modeling, ETL design, implementation and maintenance
Experience with distributed query engines and cloud data platforms (Trino, Spark, Snowflake/Redshift or equivalent) and with workflow orchestration (Azkaban, Airflow or equivalent)
Knowledge of logging, error handling, and familiarity with CI/CD concepts
Familiarity with AWS products and services
Experience with analytical model development and deployment processes
Strong communication skills and ability to collaborate effectively with stakeholders
You live our cultural values
AI Proficiency
This role uses AI as a core engineering method, not as an occasional assist. We expect proficiency across three dimensions, and we will ask you to show your work in each:
Modeling — you use AI to reason about unfamiliar data: reverse-engineering semantics from production tables, proposing metric and check definitions, and stress-testing a data model before you build it.
Implementation — you ship production code with coding agents as your default method, and can point to work that reached production this way.
Architecting — you design agentic systems themselves: multi-step workflows, tool and skill design, context and prompt structure, and the evaluation harness that determines whether a workflow is good enough to run unattended.
Most importantly, you can describe how you validate what an agent produces — what you check, what you automate, and where you decide a human must stay in the loop. In a data quality function, being fast is worth nothing if the output cannot be trusted. We care more about this judgment than about any particular tool, model or framework.
Preferred Qualifications
A software engineering background. You have built and operated production services, not only pipelines and analyses — application code, testing, code review, deployment, and responsibility for something while it is running. This matters more than usual here: the platform is a product with users, and the bar for reviewing agent-written code is set by people who have written and maintained systems themselves.
Familiarity with machine learning concepts, and a clear point of view on where predictive methods do and do not belong in a data quality context
Experience with financial data, reconciliation, ledgers, or regulated reporting
Experience building data-facing web applications or internal tools
Experience introducing data quality practices to teams that did not previously have them
Our Benefits
Rice Allowance
Transportation Allowance
Paid Vacation
Medical, Dental & Vision
Accident and Life Insurance
Employee Stock Purchase Plan (ESPP)
Mental Health & Family Forming Benefits
Our Connected Work Culture: Driving Innovation, Together
At Remitly, we believe that true innovation sparks when we come together. Our Connected Work Culture fosters dynamic in-person collaboration, where ideas ignite and challenging problems find solutions faster. For corporate team members, we have an in-office expectation of at least 50% of the time monthly, typically achieved by coming in three days a week. This creates a consistent, meaningful overlap that supports team norms and business needs. Managers also have the flexibility to set higher expectations based on their team's specific needs. These intentional in-office moments are vital for deepening relationships, fueling creativity, and ensuring your impact is felt where it matters most.
Remitly is an E-Verify Employer
At Remitly, we are dedicated to ensuring that our workplace offers equal employment opportunities to all employees and candidates, in full compliance with applicable laws and regulations.
Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
