Senior Data Engineer

We are excited to welcome you to our innovative team where we redefine cyber security expertise standards by connecting business and community through engaging hacking experiences.

Core Mission

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 will 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.

Responsibilities

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 legacy pipelines.
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 well‑scoped data products.
Continuously improve data quality, reliability, observability and cost efficiency.
Identify new data sources worth acquiring and integrate them cleanly.

Qualifications

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—production‑quality code.
Experience with ClickHouse or another columnar OLAP engine in production.
Workflow orchestration experience with Airflow (or Prefect/Dagster).
Comfortable with dbt or equivalent transformation frameworks.
Experience migrating off legacy warehouses (Snowflake, Redshift, Synapse) onto cloud‑native stacks.
Working knowledge of ML in production—feature engineering, feature stores, model deployment, drift monitoring, retraining.
Docker and Kubernetes experience.
CI/CD mindset, infrastructure‑as‑code sensibility and a bias for simple, observable systems.
Bonus: CDC tooling (Datastream, Debezium), Vertex AI / Feature Store.

Benefits

Private health care.
Paid paternity leave.
25 annual leave days.
Free lunch & snacks at the office.
Ticket Restaurant by Edenred.
Dedicated budget for training and professional development, participation in conferences.
Full access to our lab offerings for learning how to hack.
State‑of‑the‑art equipment (Mac, iPhone, mobile plan).
Flexible WFH (Hybrid Model) – fully remote also available if not in Athens.

Location & Work Mode

Europe/Greece. Choose between fully remote work across Europe or relocating to our Athens Tech Hub with relocation support.

Relocation bonuses: 10% relocation bonus on the annual salary; 50% tax reduction; accommodation support for the first few weeks.

Company Culture and Diversity Statement

At Hack The Box we are committed to fostering a diverse, inclusive, and equitable workplace. We believe that diversity enriches our performance, services, and the communities we serve. All applications are considered solely based on merit, skills, and qualifications. We do not discriminate on grounds of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We are dedicated to providing a fair and respectful work environment that reflects our values.

Show