ABOUT ENFUCE:

• Founded in 2016, Enfuce is a female-founded and led company with a unique vision: to bring the brightest minds and the best technology together to break down the barriers to prosperity.
• As a leading global card issuer and payment processor that merges innovation, security, and expertise to create modular, cloud-based payment processing capabilities, Enfuce is one of Finland’s most valuable scaleups, and is the first financial service provider in the world to be PCI-DSS certified while running its service in the public cloud.
• By focusing on collaboration, Enfuce is able to efficiently provide customers with cutting edge features – offering in-house experts and white labelled technology to help companies create scalable payment solutions with ease. Supporting debit, credit, prepaid, gift, fleet, and fuel card programmes in any form – for consumer, commercial, and B2B applications. Enfuce’s no-nonsense approach helps customers create bespoke payment solutions that are flexible, scalable, and secure.
• Holding an Electronic Money Institution (EMI) licence from the Finnish FSA and from the UK’s Financial Conduct Authority (FCA), enabling operations across Europe and the UK, Enfuce’s PCI-DSS certified platform guarantees 99.999% uptime, global scalability, and card scheme connectivity, supporting various card programmes and integration with digital wallets.
• Enfuce has raised €68.5 million in funding rounds, showcasing its industry leadership with recognitions like Visa Fintech Fast Track and Mastercard Lighthouse Development Program participation, as well as winning prestigious awards, such as the 2019 PayTech Award for Best Payments Solution, 2022 FF Award for Mobile Payments and the 2023 FF Award for Authentic ESG. Propelled by the forward-looking vision of its Co-CEOs and Nordic ingenuity, Enfuce is set to expand globally, shaping the future of payment solutions.

JOB REQUIREMENTS:

• 3+ years of experience in analytics engineering, data engineering, or similar roles.
• Experience working with other data disciplines, such as data engineering and data analytics.
• Experience with SQL, DBT, modern cloud data warehouses (e.g. Snowflake, BigQuery), self-service BI tooling (e.g. ThoughtSpot, Looker, Hex).
• Experience with Python, Jinja, Git, YAML, orchestration tools (e.g. Airflow, Dagster), and CI/CD workflows.
• Excellent communication and collaboration skills with a proactive, problem-solving mindset.
• Demonstrated ability to take ownership of projects from ideation to deployment, ensuring stakeholder alignment and timely delivery through strong planning, organisation, and prioritisation skills.

ABOUT THE ROLE:

• As an Analytics Engineer you play a key role in our team’s ability to drive value from data. You’ll join a dynamic team with expertise in Data Engineering, Data Science, Analytics Engineering, and Business Intelligence. As our Analytics Engineer you will act at the intersection between raw data and actionable insights, and it is through your collaboration with stakeholders that business requirements are translated into data solutions.
• You’ll be responsible for transforming data into reliable, high-quality, and modular models that empower a self-service analytics culture throughout the company. By collaborating with our Data Engineers, you’ll ensure that required data sources are available and structured effectively. Together with our Data Analysts, you’ll ensure stakeholders have access to trustworthy, easy-to-use, and accessible data solutions.
• If you’re passionate about working with modern data tooling, building trust in data, and enabling analytics at scale, we’d love to hear from you.

JOB ROLE:

• Translate business requirements into efficient, quality-controlled, and scalable data models that enable stakeholders to make data-driven decisions.
• Collaborate with the wider team and stakeholders to gather requirements, scope projects, and ensure alignment from start to finish. You’ll manage stakeholder expectations, communicate progress, and independently drive the execution of technical tasks to meet project milestones.
• Drive data literacy across the organisation by enabling teams to consume data effectively through clear documentation, training, and guidance.
• Build and maintain robust testing, monitoring, and validation processes to ensure data quality and reliability of data models.
• Take ownership of initiatives to enhance analytics capabilities, such as implementing new tools, optimising workflows, or introducing best practices for data modeling and governance.
• Participate in stand-ups, sprint planning, and roadmap planning to ensure alignment with team goals, strategy, and timely delivery of projects.