Job Opportunities API

Welcome! Super excited you dropped by 🥳 Let's redefine cyber security expertise standards and connect business - community through highly engaging hacking experiences. (Find out more insights about Hack The Box culture in our career site). ✨The core mission of the Senior Data Engineer: You will own and evolve our data pipelines on GCP — building new ones, hardening existing ones, improving data quality, and making clean, trustworthy data available across the organisation. You'll work end-to-end on streaming and batch pipelines, from CDC and event ingestion through transformation, serving, and the feature layer that powers our ML and AI products. Your day-to-day will include designing ELT/ETL processes on BigQuery and ClickHouse, building real-time pipelines on Pub/Sub and Kafka with Dataflow (and where it fits, Flink/Spark), orchestrating workflows with Airflow, and ensuring data is properly cleaned, modelled, and served for analytics, ML training, and online inference. You'll partner with ML engineers on feature pipelines, monitoring data drift, and keeping models well-fed and retrained as needed. You'll consume and build REST APIs, integrate with third-party SaaS sources, and treat infrastructure as code. 🏢 Location &  Work Mode: US Fully Remote 🍺 The fellowship you’ll be joining: You will be part of the Data, Analytics & AI team, collaborating closely with Infrastructure, Software Engineering, Product, and ML/AI engineers. We're in the middle of a GCP-native modernisation — migrating away from Snowflake toward BigQuery, Bigtable, Pub/Sub, and Dataflow — so we're looking for someone who's opinionated about clean architecture, allergic to over-engineering, and comfortable owning systems end-to-end. If retiring a legacy warehouse and standing up its replacement sounds like a good time, you'll fit right in. ⚔️ Technology tools & weapons you’ll be using: Cloud & warehouse: GCP, BigQuery, Bigtable, Cloud Storage Streaming & messaging: Pub/Sub, Kafka Processing: Dataflow (Apache Beam), with Flink/Spark where appropriate Orchestration: Airflow (Cloud Composer) Analytical store: ClickHouse Languages: Python, SQL Modelling & quality: dbt, data quality gates Containers & CI/CD: Docker, Kubernetes, GitHub Actions / equivalent Legacy (being retired): Snowflake 🚀 The adventures that await you after becoming Senior Data Engineer at Hack The Box: Design and build batch and streaming pipelines on Dataflow, Pub/Sub, and Kafka feeding BigQuery, Bigtable, and ClickHouse Help drive the migration off Snowflake onto our GCP-native stack — and retire shadow pipelines along the way Own the orchestration layer in Airflow, including SLAs, retries, and data quality gates Model data for analytics and for ML — including feature pipelines that serve both training and low-latency online inference Partner with ML engineers on feature stores, drift monitoring, and retraining workflows Capture requirements from stakeholders and translate them into pragmatic, well-scoped data products Continuously improve data quality, reliability, observability, and cost efficiency Identify new data sources worth acquiring and integrate them cleanly 🏆 Skills, knowledge, and experience points required to unlock the role of the Senior Data Engineer at Hack The Box: Strong data modelling and warehouse architecture skills (dimensional modelling, event-driven, lakehouse patterns) Hands-on experience with GCP data services — BigQuery is a must; Pub/Sub, Dataflow, Bigtable, Cloud Composer are strong pluses Production experience with streaming pipelines on Dataflow/Beam, Flink, or Spark Structured Streaming, ingesting from Kafka and/or Pub/Sub Solid SQL and strong Python — you write production-quality code, not just notebooks Experience with ClickHouse or another columnar OLAP engine in production Workflow orchestration experience with Airflow (or Prefect/Dagster)