Analytics Engineer – Finance

Mews

. Serve as the founding analytics engineer in Finance .

Posted 10/31/2026full-timeRemote • Czechia, France, Spain, United KingdomMid-LevelSenior💰 €46,000 - €65,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in building and optimizing ETL/ELT pipelines using DBT, Databricks, and SQL, alongside a strong understanding of data modeling and analytics architecture. Proven ability to deliver actionable insights and advocate for modern data practices within Finance.

Highest-signal resume keywords

ETL/ELT Pipeline DevelopmentSQL ProficiencyDBT ExperienceData Modeling ExpertiseAI Fluency Level 3

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

ETL/ELT Pipeline DevelopmentSQL ProficiencyPython ProficiencyData ModelingAnalytics ArchitectureData Quality AssuranceTesting PracticesAI Model DevelopmentData VisualizationOperational Efficiency

Soft Skills

Autonomous WorkProblem-SolvingCollaborationPrioritization

Tools & Technologies

DBTDatabricksPower BI

Industry Keywords

Finance Data InfrastructureData TransformationRegulated DataGoverned DataStartup Analytics Scaling

Tech Stack

Tools & technologies

CloudETLPythonSQL

About the role

Key responsibilities & impact

Serve as the founding analytics engineer in Finance
Shape Finance data infrastructure and analytical capabilities during a critical transformation
Own the analytics roadmap
Design and develop analytical features that surface actionable insights for Finance leadership
Build, optimise and maintain production-ready ETL/ELT pipelines using DBT, Databricks and SQL
Create scalable data models and analytical solutions using modern data modelling techniques
Build and champion data quality and testing practices
Collaborate across Finance to translate business requirements into technical implementations
Advocate for modern data practices and continuous improvement of the data stack
Use AI to accelerate model development and testing while critically validating its outputs
Build AI-enabled patterns and tools that improve how Finance discovers data and validates insights
Deliver operational efficiency, faster month-end close, strategic insights for capital allocation, and IPO readiness

Requirements

What you’ll need

Minimum 3 years of hands-on production experience building and optimising ETL/ELT pipelines
Proficiency in SQL and Python
Strong experience with DBT or equivalent modern data transformation tools
Experience with Databricks or similar cloud data platforms, or willingness to ramp quickly
Strong understanding of data modelling and analytics architecture
Ability to work autonomously and manage priorities amid ambiguity
Ability to break down complex problems
Demonstrated commitment to data quality, testing and accuracy
AI Fluency Level 3
Experience with data visualisation tools like Power BI (nice to have)
Background working with regulated or governed data (nice to have)
Experience scaling analytics in fast-growing startups or scale-ups (nice to have)

Benefits

Comp & perks

Unlimited paid holiday
Participation in the company share program
Paid parental leave: 6 months fully paid for primary caregivers and 2 months for secondary caregivers, available after one year of service
Annual Learning budget of €300, with more for high performers
Monthly "EDGE" time for personal development
Work from anywhere policy, with flexibility to work abroad for a few weeks each year
Relocation options available after one year
Flexible, hybrid working options
Home office setup budget
Monthly work-from-home allowance
Claude tokens for workflow automation
Location-dependent healthcare and retirement plans
Location-dependent team events, socials and other perks