Analytics Engineer - Spendesk H/F Spendesk

Transform data into business impact
Spendesk is seeking a skilled Analytics Engineer to join our growing data
organization. Reporting to the Head of Data, you will be responsible for
transforming raw data into business-ready datasets, building dimensional
models, and enabling self-service analytics across the organization.

About the role
As an Analytics Engineer, you will bridge the gap between data engineering and
data analysis/business team by creating clean, documented, and reusable
analytics assets. You'll work closely with Data Engineers, Data Scientists, and
business stakeholders to implement data quality testing, build dimensional
models, and enable data-driven decision making throughout Spendesk.
This role requires an engineer who can translate business requirements into
robust data models, implement best practices for data transformation, and
create analytics solutions that scale with our business growth.

Our tech environment

Our data platform rely on: dbt (core and Cloud), Snowflake, Looker
(original), Metabase, and Amplitude for Product analytics
For the ingestion/exposure: Airbyte (cloud), Fivetran, Airflow, Hightouch,
Segment
We use Github for versioning, CI/CD, and Synq for observability

Key Responsibilities

Data transformation & Modeling

- Transform raw data into business-ready datasets using dbt and modern
data stack tools
- Build and maintain dimensional models that serve BI and Product needs
- Implement business logic and calculations in the data transformation layer
- Create reusable analytics assets that can be leveraged across multiple use
cases
- Ensure data models follow best practices for performance, maintainability,
and scalability

Data quality & Testing

- Implement comprehensive data quality testing using dbt tests
- Develop and maintain data quality monitoring and alerting systems
- Create data validation rules that catch issues before they impact business
decisions
- Establish data quality metrics and SLAs for analytics datasets
- Collaborate with all stakeholders to resolve data quality issues at the source

Analytics enablement

- Enable self-service analytics by creating intuitive, well-documented data
models
- Partner with business and product stakeholders to understand analytics
requirements and translate them into technical solutions
- Build metric definitions and calculations that ensure consistency across the
organization
- Create data documentation and maintain data catalogs for business and
product stakeholders
- Provide training and support to stakeholders on analytics tools and data interpretation

Stakeholder collaboration

- Work closely with analysts and data scientists to provide analysis-ready
datasets
- Collaborate with business stakeholders to understand requirements and
design appropriate data solutions

- Partner with Data Engineers to ensure optimal data pipeline design and
performance
- Communicate technical concepts clearly to both technical and business
audiences

-

What we're looking for

Experience & Background

- 3-5 years of experience in analytics engineering, data analytics, or related
data roles
- Proven track record of building data models and transformations in
production environments
- Experience working with business stakeholders to translate requirements
into technical solutions
- Background in implementing data quality testing and monitoring practices

Technical Requirements

- Expert proficiency in SQL and advanced capabilities
- Hands-on experience with dbt for data transformation and modeling
- Experience with cloud data warehouses (Snowflake)
- Experience with data quality testing frameworks (e.g. dbt tests)
- Proficiency in version control systems (Git, GitHub)
- Understanding of dimensional modeling concepts and best practices

Analytics & Business Skills

- Strong understanding of business intelligence and analytics concepts
Experience with data visualization tools and self-service analytics platforms
- Ability to translate business requirements into technical data solutions
- Knowledge of statistical concepts and data analysis methodologie
- Experience creating data documentation and maintaining data catalogs

As we are an international team, please submit your application and CV in English.

About Spendesk
Spendesk is the AI-powered spend management and procurement platform that transforms company spending. By simplifying procurement, payment cards, expense management, invoice processing, and accounting automation, Spendesk sets the new standard for spending at work. Its single, intelligent solution makes efficient spending easy for employees and gives finance leaders the full visibility and control they need across all company spend, even in multi-entity structures. Trusted by thousands of companies, Spendesk supports over 200,000 users across brands such as SoundCloud, Gousto, SumUp, and Bloom & Wild. With offices in the United Kingdom, France, Spain and Germany, Spendesk also puts community at the heart of its mission.

For more information: www.spendesk.com/press

About our people & culture
We believe that people do their best work when they're given the freedom to thrive and grow. That's why liberation is at the core of everything we do. We empower Spendeskers to take ownership of their work, to navigate ambiguity, and seize every opportunity. Spendeskers come from all over the world (35+ countries and counting!) but we have plenty in common: we're bold, ever-curious, committed to kindness, and tackle every challenge with a positive mindset.

About our benefits
Our culture is built on trust, empowerment, and growth - with benefits to match!

- Flexible on-site and remote policy
- Lunch 60% funded by Spendesk (Swile Card)
- Alan Premium health insurance
- A Gymlib pass to let off steam after a productive day at work
- Access to Moka.care for emotional and mental health wellbeing
- Latest Apple equipment
- Great office snacks to fuel your day
- A positive team to work with daily!

Diversity & Inclusion

At Spendesk, we're committed to fostering an environment where all differences are encouraged, supported and celebrated. We're building our culture for everyone, with everyone. Our goal is to attract and build a diverse, equal and inclusive team, where everyone feels welcome and we truly embrace and encourage people from all backgrounds to apply.

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Transform data into business impact
Spendesk is seeking a skilled Analytics Engineer to join our growing data
organization. Reporting to the Head of Data, you will be responsible for
transforming raw data into business-ready datasets, building dimensional
models, and enabling self-service analytics across the organization.

About the role
As an Analytics Engineer, you will bridge the gap between data engineering and
data analysis/business team by creating clean, documented, and reusable
analytics assets. You'll work closely with Data Engineers, Data Scientists, and
business stakeholders to implement data quality testing, build dimensional
models, and enable data-driven decision making throughout Spendesk.
This role requires an engineer who can translate business requirements into
robust data models, implement best practices for data transformation, and
create analytics solutions that scale with our business growth.

Our tech environment

Our data platform rely on: dbt (core and Cloud), Snowflake, Looker
(original), Metabase, and Amplitude for Product analytics
For the ingestion/exposure: Airbyte (cloud), Fivetran, Airflow, Hightouch,
Segment
We use Github for versioning, CI/CD, and Synq for observability

Key Responsibilities

Data transformation & Modeling

- Transform raw data into business-ready datasets using dbt and modern
data stack tools
- Build and maintain dimensional models that serve BI and Product needs
- Implement business logic and calculations in the data transformation layer
- Create reusable analytics assets that can be leveraged across multiple use
cases
- Ensure data models follow best practices for performance, maintainability,
and scalability

Transform raw data into business-ready datasets using dbt and modern
data stack tools

Build and maintain dimensional models that serve BI and Product needs

Implement business logic and calculations in the data transformation layer

Create reusable analytics assets that can be leveraged across multiple use
cases

Ensure data models follow best practices for performance, maintainability,
and scalability

Data quality & Testing

- Implement comprehensive data quality testing using dbt tests
- Develop and maintain data quality monitoring and alerting systems
- Create data validation rules that catch issues before they impact business
decisions
- Establish data quality metrics and SLAs for analytics datasets
- Collaborate with all stakeholders to resolve data quality issues at the source

Implement comprehensive data quality testing using dbt tests

Develop and maintain data quality monitoring and alerting systems

Create data validation rules that catch issues before they impact business
decisions

Establish data quality metrics and SLAs for analytics datasets

Collaborate with all stakeholders to resolve data quality issues at the source

Analytics enablement

- Enable self-service analytics by creating intuitive, well-documented data
models
- Partner with business and product stakeholders to understand analytics
requirements and translate them into technical solutions
- Build metric definitions and calculations that ensure consistency across the
organization
- Create data documentation and maintain data catalogs for business and
product stakeholders
- Provide training and support to stakeholders on analytics tools and data interpretation

Enable self-service analytics by creating intuitive, well-documented data
models

Partner with business and product stakeholders to understand analytics
requirements and translate them into technical solutions

Build metric definitions and calculations that ensure consistency across the
organization

Create data documentation and maintain data catalogs for business and
product stakeholders

Provide training and support to stakeholders on analytics tools and data interpretation

Stakeholder collaboration

- Work closely with analysts and data scientists to provide analysis-ready
datasets
- Collaborate with business stakeholders to understand requirements and
design appropriate data solutions

Work closely with analysts and data scientists to provide analysis-ready
datasets

Collaborate with business stakeholders to understand requirements and
design appropriate data solutions

- Partner with Data Engineers to ensure optimal data pipeline design and
performance
- Communicate technical concepts clearly to both technical and business
audiences

Partner with Data Engineers to ensure optimal data pipeline design and
performance

Communicate technical concepts clearly to both technical and business
audiences

-

What we're looking for

Experience & Background

- 3-5 years of experience in analytics engineering, data analytics, or related
data roles
- Proven track record of building data models and transformations in
production environments
- Experience working with business stakeholders to translate requirements
into technical solutions
- Background in implementing data quality testing and monitoring practices

3-5 years of experience in analytics engineering, data analytics, or related
data roles

Proven track record of building data models and transformations in
production environments

Experience working with business stakeholders to translate requirements
into technical solutions

Background in implementing data quality testing and monitoring practices

Technical Requirements

- Expert proficiency in SQL and advanced capabilities
- Hands-on experience with dbt for data transformation and modeling
- Experience with cloud data warehouses (Snowflake)
- Experience with data quality testing frameworks (e.g. dbt tests)
- Proficiency in version control systems (Git, GitHub)
- Understanding of dimensional modeling concepts and best practices

Expert proficiency in SQL and advanced capabilities

Hands-on experience with dbt for data transformation and modeling

Experience with cloud data warehouses (Snowflake)

Experience with data quality testing frameworks (e.g. dbt tests)

Proficiency in version control systems (Git, GitHub)

Understanding of dimensional modeling concepts and best practices

Analytics & Business Skills

- Strong understanding of business intelligence and analytics concepts
Experience with data visualization tools and self-service analytics platforms
- Ability to translate business requirements into technical data solutions
- Knowledge of statistical concepts and data analysis methodologie
- Experience creating data documentation and maintaining data catalogs

Strong understanding of business intelligence and analytics concepts
Experience with data visualization tools and self-service analytics platforms

Ability to translate business requirements into technical data solutions

Knowledge of statistical concepts and data analysis methodologie

Experience creating data documentation and maintaining data catalogs

As we are an international team, please submit your application and CV in English.

About Spendesk
Spendesk is the AI-powered spend management and procurement platform that transforms company spending. By simplifying procurement, payment cards, expense management, invoice processing, and accounting automation, Spendesk sets the new standard for spending at work. Its single, intelligent solution makes efficient spending easy for employees and gives finance leaders the full visibility and control they need across all company spend, even in multi-entity structures. Trusted by thousands of companies, Spendesk supports over 200,000 users across brands such as SoundCloud, Gousto, SumUp, and Bloom & Wild. With offices in the United Kingdom, France, Spain and Germany, Spendesk also puts community at the heart of its mission.

For more information: www.spendesk.com/press

About our people & culture
We believe that people do their best work when they're given the freedom to thrive and grow. That's why liberation is at the core of everything we do. We empower Spendeskers to take ownership of their work, to navigate ambiguity, and seize every opportunity. Spendeskers come from all over the world (35+ countries and counting!) but we have plenty in common: we're bold, ever-curious, committed to kindness, and tackle every challenge with a positive mindset.

About our benefits
Our culture is built on trust, empowerment, and growth - with benefits to match!

- Flexible on-site and remote policy
- Lunch 60% funded by Spendesk (Swile Card)
- Alan Premium health insurance
- A Gymlib pass to let off steam after a productive day at work
- Access to Moka.care for emotional and mental health wellbeing
- Latest Apple equipment
- Great office snacks to fuel your day
- A positive team to work with daily!

Flexible on-site and remote policy

Lunch 60% funded by Spendesk (Swile Card)

Alan Premium health insurance

A Gymlib pass to let off steam after a productive day at work

Access to Moka.care for emotional and mental health wellbeing

Latest Apple equipment

Great office snacks to fuel your day

A positive team to work with daily!

Diversity & Inclusion

At Spendesk, we're committed to fostering an environment where all differences are encouraged, supported and celebrated. We're building our culture for everyone, with everyone. Our goal is to attract and build a diverse, equal and inclusive team, where everyone feels welcome and we truly embrace and encourage people from all backgrounds to apply.

-

-

-

-

-

-

is Europe's leading AI-powered spend management and procurement platform that transforms company spending. By simplifying procurement, payment cards, expense management, invoice processing, and accounting automation, Spendesk sets the new standard for spending at work for companies with up to 1,000 employees.

Trusted by thousands of companies, Spendesk supports over 200,000 users across brands such as SoundCloud, Pigment, and Bloom & Wild. With offices in the United Kingdom, France, Spain, and Germany, Spendesk also puts community at the heart of its mission with Spendesk believes that people do their best work when they're given the freedom to thrive and grow. Being bold, bringing a positive attitude, and taking full ownership are fundamental to their culture.

Ready to grow further? Check out their open roles!