About Cityswift

CitySwift is the world’s leading performance optimisation platform for public transport, enabling data-driven decision-making for some of the largest transport networks globally. Backed by over €15 million in venture capital funding, we partner with major public transport operators and government authorities, including Go-Ahead Group, Transport for London, and many more. CitySwift is experiencing accelerated growth, with 117% year-over-year revenue growth in 2025.

Our mission is to increase the adoption of sustainable public transport worldwide. Today, our platform optimises more than 3 billion passenger journeys annually, and our target is to reach 10 billion journeys by the end of 2026.

At CitySwift, you’ll have the opportunity to take ownership, make a measurable impact, and grow professionally as part of a collaborative, mission-driven team. Join us in shaping the future of public transport by driving the next phase of CitySwift’s growth.

About the Role

As an Analytics Engineer, your mission is to ensure that every data user at CitySwift is working from a single, high-quality source of truth. You will apply software engineering best practices—like version control, testing, and continuous integration—to the world of data warehousing.

In the Data Analytics team, we sit in the information layer between our tech stack and our customers. You will play a critical role in scaling our Modern Data Information Layer. You are building scalable data models that enable our platform to deliver real-time insights to the world’s largest transport operators. If you thrive on seeing the impact of data on business decisions, if you're curious about solving business problems at scale, if you want to be at the centre of AI adoption and if you love working in a creative data-led environment, then this role is for you.

Key Responsibilities

Data modelling & architecture: Build & create data models that help solve business problems. Follow team conventions and best practices for data architecture design. Understand Git workflows and raise PRs for review.
Semantic Layer & BI development: Define, build and edit semantic layer views that power customer-facing analytics such as User Apps, Dashboards, and AI tools. Create and build scalable and reusable dashboards.
Engineering collaboration & deployment: Understand the essentials of how analytics are surfaced within products. Participate in cross-team meetings and follow agreed deployment processes.
Commercial & stakeholder partnership: Understand the core commercial metrics and KPIs of the business. Respond to data requests from commercial teams. Build awareness of how data outputs are used in decision-making.
Team enablement & technical leadership: Seek support from senior colleagues, be curious and ask challenging questions. Share learnings with data peers. Follows established team processes and documentation standards.

Desired Qualifications

Experience: 3+ years in a data-centric role (Analytics, Data Engineering, or BI)
Business Acumen: Experience with solving real-world problems with data and translating data insights into outcomes.
Tooling Mastery: Advanced-level SQL (window functions, CTEs, optimisation). Deep familiarity with BigQuery or a similar cloud data warehouse (Snowflake, Redshift, etc.).
Engineering Mindset: Proficient with Git and the command line. You understand why modularity, DRY (Don't Repeat Yourself) principles, and documentation are non-negotiable.
Problem Solving: Experience handling large-scale datasets. You know how to handle time-series anomalies, null values, and complex joins without breaking the pipeline.
Communication: Ability to explain complex data to stakeholders and justify architectural decisions based on both technical performance and business needs.
Education: Degree in Data Analytics, Computer Science, Information Systems, Mathematics, or a related field—or equivalent experience scaling a modern data stack.

We value, recognise and reward our people

A role with real scope, where your impact is visible, your salary is reviewed as we grow, and there are career progression opportunities as the company scales and internationalises.
Comprehensive health and life insurance through Laya Healthcare in Ireland and Aviva in the UK.
Flexible working with hybrid working as the default in Ireland, core hours of 10am to 4pm, remote options depending on role and a work abroad programme of up to 6 weeks.
25 days annual leave from day one, increasing by half a day per year of service, plus company days off, a half day before public holidays and an end of year shutdown.
Enhanced family leave, including 6 months fully paid maternity leave and 3 weeks paid paternity leave after 18 months’ service (and wedding leave!)
And on top of all of this, the usuals done well. A matching pension scheme that increases with service, paid sick leave, bike to work scheme, wellbeing supports, and an employee referral programme with rewards of up to €4,000 (or equivalent) per referral.

#LI-Hybrid

Analytics Engineer

Benefits

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