Data Engineer at FASTMARKETS COMMODITIES SINGAPORE PTE LTD

Sofia, Sofia-City, Bulgaria -

Full Time

Start Date

Immediate

Expiry Date

11 Oct, 26

Salary

0.0

Posted On

13 Jul, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Snowflake, dbt, Dagster, CI/CD, GitHub Actions, Kubernetes, Data Modeling, ETL/ELT, Pandas, GreatExpectations

Industry

Information Services

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 Services experience (Azure, AWS, or GCP) – ability to identify and configure suitable cloud services and resources. Azure preferred but not mandatory. Solid understanding of data modelling approaches (3NF, Star Schema, Kimball/Inmon, OBT). Data Vault 2.0 knowledge is desirable. Excellent analytical and problem-solving skills with experience working with large and complex data sets Strong communication skills with attention to detail Desirable Kubernetes and container orchestration Infrastructure as Code (Terraform, Pulumi, or similar) Snowflake Cortex AI and Snowflake native app development Event streaming technologies (Azure Service Bus, Kafka, or similar) Exposure to CRM systems such as Salesforce and marketing platforms such as Marketo Experience with AI-assisted development workflows and prompt engineering Formal Qualifications Degree in a related technology field OR 3+ years’ experience in a similar role with professional certifications Snowflake – nice-to-have - SnowPro Certification If you're excited about the role but your experience, skills or qualifications don't perfectly align, we encourage you to apply anyway. Additional Information Our Values Fastmarkets people come from all different walks of life. It’s this mix of brilliant personalities, experiences and insights that gives us that warm, open, and friendly culture you can feel as soon as you meet us. But however wonderfully different we all are, there are six things we all have in common – and they form our Fastmarkets values. Created by our own employees to reflect some of the personal traits that Fastmarkets people have, our values are key to what makes our culture unique. They reflect who each of us are and they're embedded in everything we do. Our values are: METRICS DRIVEN. We use insights to improve our customers’ experience and our business performance ACCOUNTABLE. We are accountable to ourselves and those we work with: we keep our promises and get things done GROWTH MINDSET. This value enables us to be nimble to the changing realities and operate with a sense of urgency INCLUSIVE. We are inclusive and respectful, celebrating each of us and giving everyone a deep sense of belonging with the desire to bring their best self to work every day. CUSTOMER CENTRIC. We are customer-centric in all that we do COLLABORATIVE. We are collaborative, able to work across teams and capitalise on the diversity of intellect, perspectives, and experiences. We are committed to ensuring all candidates feel welcomed and supported. Should your application advance and you require accommodations for the interview process, please inform us so we can make the necessary arrangements. Reward and benefits at Fastmarkets We believe in fair pay and benefits that support you both inside and outside of work. Through Fastmarkets Rewards, you'll have access to a range of core benefits and a flexible allowance, giving you the freedom to tailor your package to suit your lifestyle, wellbeing and financial priorities. We know that everyone's needs are different, so we've designed our benefits to support our diverse global team wherever they're based. Specific benefits may vary by country and role. You’ve read a little about us – now it’s over to you! If you like what you’ve read so far and think you can see yourself as a Fastmarkets person, it’s time to fill in your application form. This form is an important part of the selection process: it’s used to determine whether or not you’ll be chosen to have an interview and acts as a basis for the questions we’ll ask you on the day. It’s vital that you try to capture all the relevant information we have asked for on the form so we can get a good feel for who you are and why you’re great. Department: Technology Employment Type: Permanent

How To Apply:

Incase you would like to apply to this job directly from the source, please click here

Responsibilities

Design, develop, and maintain scalable data pipelines and transformations using dbt and Python. Implement DataOps practices, including automated data quality checks and observability via Dagster.