Data Engineer
Company: Fastmarkets
Role summary
Data Engineer is a role at Fastmarkets in Sofia, Sofia-City, Bulgaria (on-site). Posted 2026-08-12. Experience level: 2-5.
- Job title
- Data Engineer
- Company
- Fastmarkets
- Location
- Sofia, Sofia-City, Bulgaria
- Work arrangement
- on-site
- Category
- Data Science
- Experience level
- 2-5
- Date posted
- 2026-08-12
Job description
Company Description
Fastmarkets is an industry-leading price-reporting agency (PRA) and information provider for global commodities, providing price data, news, analytics and events for the agriculture, forest products, metals and mining and new-generation energy markets.
Fastmarkets' data is critical for customers seeking to understand and predict dynamic, sometimes opaque markets, enabling trading and risk management. Fastmarkets is a global business with a history dating back to 1865 and is built on trust and deep market knowledge. It has more than 700 employees spread across global locations in the UK, US, China, India, Singapore, Brazil, Belgium, Bulgaria, Finland and beyond.
Job Description
The Role
The Fastmarkets Data Platform team sits within the Technology function and is responsible for developing and delivering the company’s data strategy through data engineering, insights, analytics, and business intelligence. The team has built the organisation’s entire modern data platform from scratch and continues to evolve it to support Fastmarkets’ growth and AI ambitions.
Reporting directly into the Head of Data Architecture, Engineering & AI, we are looking for the right candidate to model and build our data pipelines and transformations. This is a fantastic opportunity to join us and contribute to a high-performing workstream delivering transformational change across both BI and our monetizable data assets. You will work with modern technologies and frameworks – with input to help deliver and adapt processes that enable a true “DataOps” environment and development experience.
The Data Engineer will ensure that data is cleansed, tested, and delivered in accordance with Fastmarkets and industry best practice. In addition, the Data Engineer will enable monitoring via the observability platform and ensure that notifications and alerts are appropriately configured.
We actively leverage AI tools across the data engineering workflow, including Anthropic Claude for documentation, code generation, and code review, as well as Snowflake Cortex AI capabilities for in-platform intelligence. The successful candidate will be expected to embrace AI-assisted development as a core part of how we work.
The role requires a high standard of expertise in SQL and Python as well as specialist knowledge of modern approaches to delivering data projects using a code-first approach.
Principal Accountabilities
Design, develop, and maintain scalable and efficient data pipelines from a wide variety of sources
Use dbt (Data Build Tool) to transform data through the various layers (Cleansed, Conformed, Presentation etc)
Ability to write custom connectors (Python) and leverage out-of-the-box data-loading tools
Operationalise enterprise data model by curating appropriate data models to service reporting, analytics, and data science use cases
Embed real-time, automated data quality checks, validations, exception handling, and alerting across all data pipelines
Work within Dagster as the primary orchestration and observability platform for all data pipelines
Manage CI/CD workflows using GitHub, GitHub Actions, and Kubernetes
Use zero-copy cloning and containerised on-demand development environments
Implement and review RBAC policies within Snowflake and related platforms
Embrace DataOps and a code-first approach to all data engineering work
Identify and promote best practices in data engineering; recommend improvements to existing processes and systems
Leverage AI-assisted development tools (Anthropic Claude, GitHub Copilot) to accelerate delivery and improve code quality
Excellent problem-solving skills and ability to embrace change
Effective communication and collaboration skills
Natural self-starter, with enthusiasm for learning and research
KEY INTERFACES
Internal:
Head of Data Architecture, Engineering & AI
Data Engineering team
Technology & Infrastructure teams
Editorial and Pricing teams
BI & Analytics teams & stakeholders across the business
Product and Commercial teams
External:
Consultancy partners supporting platform delivery
Snowflake technical account team
Third-party vendor and tooling support
Qualifications
We recruit talented, dynamic people with diverse backgrounds and experiences, all united by a belief in our mission to provide the world’s leading and most trusted price reporting, events, and intelligence service for the markets we serve. We’re proud to be an equal opportunities employer and are committed to creating a fully inclusive workplace, where everyone feels able to participate and contribute meaningfully.
If you are open-minded, curious, resilient, solutions-oriented and committed to promoting equality, then read on.
KNOWLEDGE, EXPERIENCE AND SKILLS
We are looking for an individual who is highly motivated, driven, and have a passion to be part of a fast-paced, successful team. Being a strong team player is also important as well as someone who is happy to work flexibly.
Essential
Advanced SQL Expertise – CTEs, stored procedures, query tuning – across more than one flavour of SQL (e.g. Snowflake, MSSQL). Snowflake experience is MANDATORY.
dbt (Data Build Tool) and Jinja templating
Extensive hands-on experience with Snowflake as a cloud data warehouse, including Snowpark for Python-based transformations
Experience with ELT/ETL ingestion tools such as Fivetran, Airbyte, or similar connector-based platforms
Python data pipelines and libraries including Pandas and GreatExpectations for data quality
Experience with Python-based orchestration platforms such as Dagster, Apache Airflow, or Prefect
API integration and JSON parsing/transformation
Git version control (branching, pull requests, merge conflict resolution)
CI/CD principles and experience (GitHub Actions, Azure DevOps)
Cloud Service