Today the platform is SQL Server-heavy, and part of this role is migrating business and data logic out of legacy stored procedures into testable Python - parameterized SQL for retrieval, pandas for computation and reshaping. As we evolve, we intend to grow well beyond a single database - incorporating additional and modern data sources (for example, Snowflake, which the API’’s SQLAlchemy-based connection registry is already designed to add) and the patterns needed to serve them through a unified API. This is a foundational, shaping role: you will help define the architecture and direction of that next-generation platform, not just maintain what exists., We are seeking a Software Engineer with a strong data-engineering focus to join the Data Team. The role is primarily focused on the data API, but it is a team role rather than a single-service one - you will work across the data platform as it grows. This is backend- and data-centric work: you will spend more time on data correctness, performance, and the movement and reconciliation of large datasets across heterogeneous sources than on any single framework or UI library. We value depth in the core technologies and engineering fundamentals over expertise in any specific component, and we expect enough Azure and DevOps capability to deploy and operate what you build.

Software Engineering, Software Development, Application Programming Interface (API), Snowflake Schema, Data Sets, Software Engineering, DevOps, Reconciliation, Microsoft Windows Azure, User Interface/Experience (UI/UX), Bachelor’’s degree in Software Engineering/development, Computer Science, or related field.

3 years of experience in software development.

Strong proficiency in Python (3.12+) backend development - FastAPI, Pydantic v2, async/await - and T-SQL, with deep comfort in the data and service layers of an enterprise application. (Breadth and fundamentals matter more than any specific library or framework.)

Expert-level SQL Server and data engineering: parameterized query authoring, query optimization and execution-plan analysis, indexing strategy, set-based processing, and bulk / ETL data movement and large-dataset performance tuning - plus comfort migrating logic out of legacy stored procedures into Python.

Exposure to modern cloud data platforms and warehouses (e.g. Snowflake) and an interest in integrating multiple, heterogeneous data sources - each just another SQLAlchemy dialect - behind a unified API.

What do we offer?

Confluence offers generous benefit packages for team members. As a growing, global organization, we are always looking for ways to ensure that our employees can access benefits that matter to them and their families. This includes:

Generous Time Off packages including additional half days with each public holiday in your location.

Global Career Development opportunities

Social Events

Referral Bonus scheme - Upto $3,000 per successful referral

Plus many more!

More about the Location

We offer flexible working options for all employees.

LI-US -Remote (Eastern Standard Time Zone)

Values

We look for people who align with our 4 values.

Integrity

Face reality with honesty, courage and accountability

Imagination

Deal creatively with challenges and envision what the world could be

Discipline

Build good habits into reflexes which become a part of our life

Service

Committed to the success of others

At Confluence, we’ve always been driven by a commitment to innovation, precision, and partnership in the investment data space. Our global footprint now spans multiple countries, giving our employees the opportunity to get exposure to other countries and cultures. And it stands to reason that none of this would have been possible without the hundreds of hard-working employees who work at Confluence.

More about the role & team

The Data Team is building the next-generation data platform - a multi-tenant platform that will become the shared data layer behind our applications. At the heart of that platform is a Python data API built on a layered router service repository architecture, containerized with Docker and deployed entirely through infrastructure-as-code.