Booking Holdings Romania - Senior Data Engineer I

Booking Holdings Romania is a Center of Excellence based in Bucharest, Romania and was created to support the increasing business demands of the Booking Holdings Brands. The Center of Excellence provides access to specialized and highly skilled talent, leading industry best practices, and collaboration opportunities across all of our Brands.

As part of our Booking Holdings Romania team, you will have the opportunity to be a part of the world’s leading provider of online travel, with a mission of making it easier for everyone to experience the world through five-primary consumer facing brands: Booking.com, Priceline, Agoda, KAYAK and OpenTable.

The Senior Data Engineer I is a fully independent technical contributor who owns complex data products end-to-end and shapes how the team builds, runs and operates them. This role carries a distinct DevOps / DataOps / Infrastructure flavour: alongside building data pipelines and models on Snowflake, dbt and Dagster, the Senior Data Engineer I drives the underlying platform — system architecture for data workloads, containerization (Docker, Kubernetes), CI/CD pipelines on Harness, infrastructure-as-code (Terraform), AWS infrastructure, secrets and access management (HashiCorp Vault, AWS Secrets Manager), and end-to-end observability of the data platform.

Working on cross-brand data, reporting and analytics for business areas such as Finance, FP&A, Treasury, Procurement, Market Intelligence and others, the Senior Data Engineer I raises the technical bar across the team, mentors mid-level engineers, and partners with the Solutions Architect and the Product Manager to translate business priorities into resilient, auditable and SOX-compliant data solutions.

This role provides a hybrid way of working with an onsite presence of 2 days/week.

Key Job Responsibilities and Duties

• Platform & Pipeline Ownership: Owns critical data pipelines and the underlying platform end-to-end on Snowflake, dbt, Dagster, AWS, Kubernetes and Terraform — including system design, implementation, performance, cost, reliability and incident handling.

• System Architecture for Data Workloads: Designs the system architecture for data services and workloads on the team — how containers, orchestrators, schedulers, secrets and storage fit together — and evolves it as new use cases land. Partners closely with the Solutions Architect on cross-cutting decisions.

• Containerization & Kubernetes: Owns Docker images for the team's data workloads and the Kubernetes deployments that run them. Designs manifests / Helm charts, manages resource sizing, autoscaling, network policies and storage classes for data pipelines on K8s.

• CI/CD on Harness: Designs and improves CI/CD pipelines on Harness for dbt projects, Dagster code, container images and infrastructure repositories. Hardens deployment processes, manages multi-environment promotion (dev/test/prod), and codifies safe rollback and approval gates.

• Infrastructure as Code & Cloud: Owns Terraform modules for the team's AWS footprint — networking (VPC, subnets, security groups), compute, IAM, storage and supporting services. Reviews infrastructure changes from mid-level engineers.

• Secrets & Access Management: Owns secrets handling and access patterns for the team using HashiCorp Vault and AWS Secrets Manager — least-privilege configurations, rotation policies, audit trails, integration with K8s and CI/CD.

• Snowflake Engineering Depth: Acts as a strong Snowflake practitioner: performance tuning, warehouse sizing, clustering, RBAC, cost optimization and governance, partnering with the Solutions Architect on platform-level decisions.

• Python for Dagster & Tooling: Writes high-quality, object-oriented Python for Dagster (assets, sensors, IO managers, resources) and for the team's operational tooling; sets patterns and reviews code from mid-level engineers.

• Observability & Reliability: Defines and tracks SLIs / SLOs for data pipelines and platform components, implements proactive monitoring, alerting and runbooks, and leads incident root-cause analysis and post-mortems on the data side.

• Risk, Control & SOX: Designs and operates data flows in line with Risk & Control requirements (auditability, lineage, access control, segregation of duties) and supports SOX-relevant reporting use cases.

• Technical Leadership & Mentoring: Reviews designs and pull requests for the team, mentors mid-level engineers on engineering and operational excellence, and helps shape technical standards together with the Solutions Architect.

• Stakeholder Partnership: Partners with the Product Manager, Senior BAs and engineering peers in the brand teams to scope and prioritize work, and represents the team in technical discussions with stakeholders across the supported business areas.

Role Qualifications and Requirements

• Deep understanding of data warehousing and dimensional modeling on cloud platforms, preferably Snowflake; familiarity with Data Vault is a nice to have (*).

• Deep understanding of system architecture for data workloads — how containers, orchestrators, schedulers, secrets, networking and storage fit together.

• Strong understanding of CI/CD, release management and DataOps principles, including multi-environment promotion patterns and rollback strategies.

• Strong understanding of containerization patterns and Kubernetes for running data workloads (deployments, jobs, cronjobs, resource limits, autoscaling).

• Strong understanding of cloud architecture patterns on AWS for data workloads (VPC, IAM, S3, compute, networking, security).

• Strong understanding of secrets management and least-privilege access patterns using Vault and / or AWS Secrets Manager.

• Strong understanding of data privacy, security, GDPR/PII and access control (RBAC) on cloud data platforms.

• Experience in one or more relevant business domains — such as Finance, FP&A, Treasury, Procurement, Market Intelligence — or transferable experience from comparable domains.

• Preferred (*): Working knowledge of Risk & Control / SOX requirements for financial and regulatory data and reporting.

• Advanced Snowflake: performance tuning, clustering, RBAC, cost optimization, governance.

• Advanced dbt: modular design, macros, testing, documentation, project hygiene.

• Advanced Dagster (or Airflow / equivalent orchestrator): assets, partitions, sensors, IO managers, resources.

• Strong object-oriented Python for orchestration, tooling and data engineering.

• Strong Kubernetes for data workloads: deployments, jobs, cronjobs, services, ingresses, resource sizing, autoscaling; comfortable with Helm or Kustomize.

• Strong Docker: image design, multi-stage builds, layering, security and registry workflows.

• Strong CI/CD experience on Harness (or comparable enterprise CI/CD: GitHub Actions, GitLab CI, ArgoCD) — pipeline design, approval gates, secrets injection, environment promotion.

• Strong AWS hands-on for data workloads: S3, IAM, networking (VPC, security groups), Lambda, Glue, CloudWatch.

• Strong Terraform: modules, state management, multi-environment patterns, drift detection.

• Hands-on experience with secrets management — HashiCorp Vault and / or AWS Secrets Manager — including integration with K8s and CI/CD.

• Strong Git workflows and code review discipline.

• Awareness of BI / Dashboard concepts and semantic layers — sufficient to collaborate with the Reporting team and to design the data layer feeding them.

• Work experience with Streamlit (or similar lightweight data app frameworks) is a plus (*).

• Hands-on experience using AI / LLM-based tools to accelerate engineering work — code generation, code review, debugging, documentation, data exploration — is a plus (*).

• Owns complex, cross-source pipelines and platform components end-to-end with minimal oversight.

• Designs system architecture for data workloads pragmatically — choosing between K8s, serverless, managed services based on operational reality, cost and team capability.

• Makes pragmatic trade-offs between speed, scalability, cost and operability and explains them clearly.

• Manages stakeholders across the data team, brand teams, R&C and Infrastructure with confidence.

• Mentors mid-level engineers on engineering and DataOps practices, and raises the technical bar through reviews and pairing.

• Excellent English communication — able to engage technical and non-technical stakeholders alike.

• Proven ability to drive technical change and impact across multiple teams.

Benefits & Perks

• Contributing to a high scale, complex, world renowned product and seeing real-time impact of your work on millions of travelers worldwide

• Working in a fast-paced and performance driven culture

• Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences and active community participation

• Competitive compensation and benefits package

• Vast amounts of data to validate your ideas and the opportunity to experiment with real users

Booking Holdings is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive.

Pre-Employment Screening

If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.