Senior Data Platform Engineer

To build and evolve a self-service data platform that empowers engineering teams, analysts, and data scientists to build, discover, and scale their own data initiatives with built-in governance, observability, and minimal friction.

• The full lifecycle of data across the company: extraction, ingestion, landing, transformation, governance, and observability

• The data infrastructure and platform capabilities that enable teams to create and scale their own data products

• Core platform components that ensure data quality, compliance, lineage, and discoverability

• The evolution of our data platform into a self-service ecosystem where teams can autonomously manage their data lifecycle

The Data Platform team is a key part of the Data organization, which also includes the Head of Data, Data Governance Lead, Data Science & AI, and Data Analytics teams. 

The Data Platform team currently consists of a Data Platform Lead, four Data Engineers, and one MLOps Engineer. They collaborate closely with the Infrastructure Platform team and the rest of the Data organization to build and evolve the company's data platform.

• Platform mindset: we build capabilities and tooling, not one-off solutions

• Engineers treat internal teams as platform customers

• Strong collaboration with Infrastructure Platform, Data Science & AI, and Data Analytics teams

• Infrastructure-as-Code and automation are core engineering principles

• We are transitioning from a reactive ticket-based model to a product-oriented platform team

Our data platform runs on AWS with Kubernetes (EKS) and everything managed via Terraform and Helm. CI/CD is handled with GitHub Actions and Jenkins. We ingest data from multiple sources using Airbyte, store it in S3 and Redshift, transform it with dbt, and orchestrate pipelines with Airflow. For governance and discovery, we use OpenMetadata, while analytics are delivered through Metabase. Observability is implemented with Prometheus, Grafana, Thanos, Elastic, and Tempo, and our infrastructure and automation scripts are mainly written in Python, Terraform, and Helm.

• 7+ years of experience in Data Engineering, Data Platform Engineering, or Infrastructure Engineering

• Strong experience building and maintaining data platforms or distributed systems

• Experience with AWS cloud environments

• Solid experience with Kubernetes and containerized infrastructure

• Strong experience with Infrastructure as Code (Terraform, Helm)

• Experience implementing observability, monitoring, logging, and alerting systems

• Strong engineering rigor: version control, testing, modular design, and documentation

• High autonomy, ownership, and ability to drive technical decisions

• Proficiency in English for daily communication, documentation, and technical discussions

• Experience working with AI augmentation tools for daily and engineering tasks.

• Experience implementing data observability frameworks (Elementary, Great Expectations, etc.)

• Experience implementing Change Data Capture (CDC) pipelines

• Experience with Airflow or other DAG orchestration tools

• Experience building self-service platforms for data teams

• Familiarity with modern data lake formats such as Apache Iceberg
  

1. Interview with People Team

2. Technical take-home assessment (async)

3. Live Peer review of the assessment

4. Meet the team

We kindly ask that you submit your CV in English as it is the official language of our community.

We promote equal opportunity to all, regardless of age, color, gender identity, medical condition, physical or mental disability, race, religion, sexual orientation, or any other characteristic. We have an inclusive environment, and respect is above all.