Analytics Engineer at Veriff

, , -

Full Time

Start Date

Immediate

Expiry Date

01 Jan, 26

Salary

0.0

Posted On

03 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, dbt, Data Pipelines, Cloud-Based Data, Data Modeling, Data Governance, Data Observability, Cross-Functional Collaboration, Self-Service Analytics, Access Control, Permissioning, Analytical Skills, Documentation, Testing, Stakeholder Management

Industry

Software Development

Description

About Veriff Veriff is solving the online identity crisis — empowering trust in the digital world through secure, scalable identity verification. We work with some of the world’s most innovative companies, protecting millions of users globally. The Operations & Analytics team powers Veriff’s business engine. We’re tackling the identity crisis at scale and deploying operational excellence to keep Veriff on the cutting edge. It’s a fast-paced market with evolving challenges — and we’re looking for fresh talent to help fill the gaps. Our team blends operational insight and technical depth, combining systems, processes, and analytics to ensure Veriff runs efficiently and intelligently. About the Role As an Analytics Engineer, you'll be responsible for designing clean, reusable data models that unlock operational insights and power data-driven tools — from internal and external self-service interfaces to models that support analytics across Product, Finance, Sales, Marketing and Operations. You’ll work cross-functionally across Data Insights, Product & Engineering, and Business to build analytics systems that scale — focused on real-world use cases. You’ll help us protect honest people online by: Build and maintain sustainable dbt models aligned with business logic and stakeholder workflows Own model development for core operational and customer-facing analytics use cases Support the self-service tooling initiative by building reliable, permissioned data foundations Translate complex raw datasets into clear, documented, analyst-ready structures Define and enforce modeling and documentation standards across the Data Insights team Collaborate with Data Analysts, Data Scientists, Product Managers, and Data Engineers to deliver full-stack data solutions Contribute to long-term improvements in data governance, observability, and testing Reduce single points of failure by distributing model ownership and formalizing critical assets You are the right future Veriffian for the job if: Have 3+ years of experience in analytics engineering or BI development with strong SQL and solid intermediate level Python proficiency Have production experience with dbt in a version-controlled environment Understand scalable data pipelines and cloud-based data environments (e.g. Redshift, BigQuery, Snowflake) Know how to build models that are reusable, auditable, and stakeholder-aligned Care deeply about sustainable pipelines, naming conventions, testing, and metadata Translate business problems into scalable model logic Communicate clearly across technical and non-technical teams Thrive in cross-functional and hybrid work environments You’re an especially awesome match if you have: Experience designing self-service analytics platforms Familiarity with data quality and observability tools Understanding of access control and permissioning in analytics systems What Veriff Offers You A high-impact role shaping analytics foundations for mission-critical operations The opportunity to own major data model domains and unlock scalable self-service A culture that values engineering discipline, systems thinking, and shared ownership Flexibility to work from Tallinn in a Hybrid model or remotely from Spain Competitive salary, stock options, and benefits that support your growth and well-being A cross-functional, forward-thinking team committed to trust, clarity, and scale Why Veriff? We help companies all over the world connect with honest people. Our software verifies over 10,000 government-issued documents from more than 190 countries — and this is growing fast! That's millions of verified identities a year and countless people working behind the scenes to help make the lives of millions, and eventually billions, of people safer online. We are a force for good and want to be the standard for trust online. We're a diverse team of over 40 nationalities coming together to solve one of the world's most pressing problems. When you join Team Veriff, we offer you the opportunity to have a real impact and advance your career whilst looking after you along the way with a range of benefits designed with you in mind. Some of our favourites include: Six weeks of fully paid sabbatical leave after reaching your 3rd work anniversary Comprehensive relocation support to Spain or Estonia One day per year to dedicate to a charity of your choice Full flexibility to work from home or our pet friendly offices Stock options that ensure you share in our success Extensive medical, wellness and L&D coverage to ensure you're feeling great physically and mentally With backing from investors such as Accel, IVP, Tiger, Taavet Hinrikus, Ashton Kutcher, and Paul Buchheit, and having received unicorn status, we're well positioned to achieve our mission. However we need people like you to ensure it happens. Be a force for good and join Veriff! We are an Equal Opportunities employer committed to a diverse and representative team. Different opinions, perspectives and personalities push us forward. We want to hear from people who are passionate about their work and align with our values. Regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability. We also know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates - so rest assured, whoever you are, we want to hear from you. #SPBTAL

Responsibilities

As an Analytics Engineer, you'll design clean, reusable data models that unlock operational insights and power data-driven tools. You'll collaborate across teams to build scalable analytics systems focused on real-world use cases.