Data Analytics Engineer (Treasury Data Science & Analytics)

Booking.com; Amsterdam; On-site; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Health insurance

Pension plan

Life insurance

Annual paid time off

On-site meals and snacks

Job summary

Booking.com is seeking a Data Analytics Engineer I to contribute to the design, development and maintenance of analytical data models, processing pipelines and reusable data assets. This hands-on role sits at the intersection of analytics and engineering with a focus on migrating and modernising the team’s analytical frameworks.

You will own migration deliverables, establish consistent practices for deployment, monitoring and maintenance, and work with finance stakeholders as the first

Qualifications

• Experience with cloud services for data processing or storage.
• 1–3 years of relevant experience in Data Analytics Engineering, Analytics Engineering, Data Engineering, Data Warehousing or related roles.
• Programming in Python with maintainable, reusable code.
• Strong SQL skills with data transformation and discrepancy investigation.

Responsibilities

• Migrate and modernise analytical frameworks.
• Build reusable data assets and pipelines for analytics.
• Own workflow migration, scheduling, monitoring and incident support.
• Collaborate with data scientists and analysts to ensure data quality and metrics.

Skills

Python programming

SQL proficiency

Stakeholder management

Data modeling

Data governance

Cloud services

Data pipelines

Communication skills

Education

Bachelor’s degree in Computer Science or related field

Tools

Docker

Kubernetes

Snowflake

dbt

Git

Job description

• As a Data Analytics Engineer I in the Treasury Data Science & Analytics team, you will contribute to the design, development and maintenance of analytical data models, processing pipelines and reusable data assets
• This is a hands‑on data engineering role which sits at the intersection of analytics and engineering with a strong focus on migrating and modernising the team’s analytical frameworks.
• You will take ownership of defined migration deliverables and help establish consistent practices for developing, deploying, scheduling, monitoring and maintaining pipelines
• As the first and only Analytical Engineer on the team, you should enjoy working independently while partnering closely with finance business stakeholders
• Working with data scientists and analysts, you will build reusable components, strengthen data quality controls, improve the reliability and own the maintenance of existing solutions.
• You will work within engineering standards, with guidance on complex design decisions
• Take ownership of workflow migration and modernisation
• Build and optimize analytical data assets and pipelines using dbt and PySpark, improving execution time and resource efficiency. Integrate data from multiple sources and prepare curated datasets with consistent business definitions and clearly defined granularity, historical coverage and schedules
• Help establish consistent workflow management across the team, covering scheduling, dependencies, retries, backfills, health monitoring and alerting. Take responsibility for assigned workflows and support incident investigation and resolution
• Implement automated data quality controls, including recency, completeness, uniqueness, reconciliation, schema-change detection and validation of critical business metrics
• Develop and maintain data processing and integration components for analytical applications and operational automation, adapting solutions as source systems and business requirements evolve
• Build and maintain Snowflake semantic views and implement agreed metric definitions to support self‑service and AI‑assisted analytics. Support data scientists and analysts with the data models behind dashboards and reports, helping validate data consistency and metric accuracy
• Establish data governance and access‑control requirements, maintaining clear data definitions, lineage and technical documentation

Benefits

• Health insurance
• Free access to Headspace for you and your loved ones
• Global Employee Assistance Program
• Meditation and Breastfeeding rooms at the office
• Booking Cares - 2 days per year to volunteer and learn
• Life insurance
• Disability insurance
• Pension plan
• Annual paid time off
• Parental leave - 22 weeks
• Grandparent leave - 10 days
• Care leave - 10 days
• Bereavement leave - up to 4 weeks
• Anniversary leave
• Working from Home Furniture and Ergonomic Support
• Working from Abroad - up to 20 days per year
• Discounts & Wallet credits to spend on our products
• Upgrade to Booking.com Genius Level 3
• Friends & Family Booking.com discount vouchers
• Free access to online learning platforms
• Development and mentorship programs to support career growth
• Access to trainings and workshops
• Team development opportunities
• Local discount programs
• Game rooms in offices
• On‑site meals, coffee and snacks including vegan options

Experience working with cloud services for data processing or storage, and practical experience deploying or troubleshooting containerized workloads within existing Docker/Kubernetes environments1–3 years of relevant experience in Data Analytics Engineering, Analytics Engineering, Data Engineering, Data Warehousing or a related data or software roleProgramming experience in Python, with the ability to write clear, maintainable and reusable codePractical experience with analytical data modelling, including data granularity, relationships, aggregation and historical dataUnderstanding of data governance and security fundamentals, including documentation, traceability and access controlsExperience implementing automated data quality checks and validating outputs against source dataExperience working with relational databases or cloud data warehouses; familiarity with Snowflake is beneficialExperience using Git, code reviews, automated testing and existing CI/CD pipelinesBachelor’s degree or higher in Computer Science or a related field, or equivalent professional experienceStrong SQL skills, including combining datasets, implementing transformation logic and investigating discrepanciesStakeholder-management and communication skills, including the ability to explain complex technical decisions and trade-offsExperience building data transformation pipelines using dbt or a comparable frameworkExperience exploring and visualizing data and explaining findings to business stakeholdersExperience supporting scheduled workflows and using logs, monitoring and alerts to investigate issuesSQL-based data transformation using dbt or a comparable framework; Python programmingPractical experience with cloud services and containerized workloads using Docker/KubernetesData exploration, visualization and stakeholder communicationData quality controls and reconciliationData pipeline design, API integration, workflow migration and orchestrationProduction monitoring, troubleshooting, performance and cost optimisationBasic understanding of statistical modelling and machine learning conceptsData governance, access controls and technical documentationAnalytical data modelling and warehousing, including dimensional modellingSoftware engineering practices: Git, code reviews, automated testing and CI/CDExperience with SnowflakeDistributed processing using Apache Spark through PySpark or Spark SQLReporting, monitoring and analytical application tools: Tableau, Grafana, Streamlit or similarSnowflake semantic views or comparable semantic‑layer technologies for self‑service and AI‑assisted analyticsExperience preparing data for forecasting and predictive models