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Fastmarkets

Cross-commodity price reporting and market data

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeSofia, BulgariaNo salary listed

About the Job

Requirements

  • Advanced SQL expertise, including common table expressions, stored procedures, and query tuning across more than one SQL flavor; Snowflake experience is mandatory.
  • Experience with 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 extract, load, and transform or extract, transform, and load ingestion tools such as Fivetran, Airbyte, or similar connector-based platforms.
  • Experience building Python data pipelines and using libraries including Pandas and Great Expectations for data quality.
  • Experience with Python-based orchestration platforms such as Dagster, Apache Airflow, or Prefect.
  • Experience with API integration and JSON parsing and transformation.
  • Experience with Git version control, including branching, pull requests, and merge conflict resolution.
  • Knowledge of continuous integration and continuous delivery principles and experience with GitHub Actions or Azure DevOps.
  • Cloud services experience with Azure, AWS, or GCP, including the ability to identify and configure suitable cloud services and resources; Azure is preferred but not mandatory.
  • Solid understanding of data modeling approaches, including 3NF, Star Schema, Kimball/Inmon, and OBT.
  • Strong analytical and problem-solving skills and experience working with large and complex data sets.
  • Strong communication skills and attention to detail.
  • A degree in a related technology field, or at least three years of experience in a similar role with professional certifications.

Responsibilities

  • Design, develop, and maintain scalable and efficient data pipelines from a wide variety of sources.
  • Use dbt to transform data through layers such as Cleansed, Conformed, and Presentation.
  • Write custom connectors in Python and use out-of-the-box data-loading tools.
  • Operationalize the enterprise data model by curating appropriate data models for reporting, analytics, and data science use cases.
  • Embed real-time automated data quality checks, validations, exception handling, and alerting across data pipelines.
  • Work within Dagster as the primary orchestration and observability platform for data pipelines.
  • Manage continuous integration and continuous delivery workflows using GitHub, GitHub Actions, and Kubernetes.
  • Use zero-copy cloning and containerized on-demand development environments.
  • Implement and review role-based access control policies within Snowflake and related platforms.
  • Apply DataOps and a code-first approach to data engineering work.
  • Identify and promote data engineering best practices and recommend improvements to existing processes and systems.
  • Use AI-assisted development tools, including Anthropic Claude and GitHub Copilot, to accelerate delivery and improve code quality.
  • Ensure data is cleansed, tested, and delivered in accordance with company and industry best practices.
  • Enable monitoring through the observability platform and ensure notifications and alerts are appropriately configured.

Desired Qualifications

  • Knowledge of Data Vault 2.0.
  • Kubernetes and container orchestration experience.
  • Infrastructure as Code experience with Terraform, Pulumi, or similar tools.
  • Snowflake Cortex AI and Snowflake native app development experience.
  • Event streaming technology experience with Azure Service Bus, Kafka, or similar tools.
  • Exposure to CRM systems such as Salesforce and marketing platforms such as Marketo.
  • Experience with AI-assisted development workflows and prompt engineering.
  • Snowflake SnowPro certification.

About the Company

Fastmarkets

Cross-commodity price reporting and market data

Fastmarkets is a cross-commodity price reporting agency that provides price data, forecasts, market analyses, and industry events across agriculture, forest products, metals and mining, and energy transition markets. Its products come from a collection of established brands and help customers understand complex markets and make strategic decisions. The company combines authoritative price reporting with market intelligence and events to support transparency in commodity markets. Its goal is to create transparent markets that balance supply and demand and enable investments toward a more sustainable, low-carbon economy.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
1882

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