Senior Data Engineer, Datacraft team

Become a Senior Data Engineer for Bloomreach!

Join our newly formed Datacraft team — the team building the next-generation data platform that powers internal Databricks, the Loomi Marketing Agent with Data Insights capability for Bloomreach Marketing platform. Your engineering work will directly impact how hundreds of enterprise customers access, understand, and activate their Bloomreach data internally and with data share in Databricks and BigQuery.

The base salary range for this position at the P3 / Senior Software Engineer level is CZK 1 300 000 - CZK 1 600 000. The pay range actually offered will take into account a variety of potential factors considered in compensation, including but not limited to skills, qualifications, geographic location, accomplishments, experience, credentials, internal equity and business needs, and may vary from the range listed above. Working in one of our Central European offices (Bratislava, Brno or Prague) or from home on a full-time basis, you'll become a core part of the Engineering team.

What challenge awaits you?

You will join the Datacraft team as one of its founding engineers. Datacraft is a new team in the Engagement pillar, established to tackle three interconnected domains:

• Data Warehouses (~60% of team domain) — making Bloomreach data first-class in customer Databricks. The strategic goal for 27 is to use Databricks to exponentially accelerate data adoption — both for customers who want their data outside Bloomreach and for Bloomreach itself to build analytics faster.
• Dashboards & Analytics Stack (~20%) — moving Marketing reporting and dashboarding from the proprietary stack onto Databrick.

Datacraft is an AI-first team. We believe code is a commodity and expect every engineer to fluently use coding agents (e.g., Cursor, Claude Code, Copilot, Gemini CLI) as a core part of their daily workflow. The ability to leverage AI tooling to accelerate development, prototyping, and problem-solving is not optional — it's foundational. We rely heavily on knowledge graphs and spec driven development.

As a P3 (Senior) engineer at Bloomreach you are an independent professional — expert in at least one component, able to decompose objectives into tasks, and lead small projects end-to-end with minimal day-to-day guidance.

Your job will be to:

• a. Build the Databricks data platform — Design data pipelines (Kafka → Flink -> GCS Iceberg → Databricks) following medallion architecture using Databricks notebooks and Spark Declarative Pipeline. Own data models and ETL mutations for ID resolution and consent semantics. Maintain orchestration (Airflow / Cloud Composer) and monitoring.
  
  
• b. Co-build dashboards & analytics stack — Design canonical metrics and models on Databricks, support semantic layers and BI tools (Cube, Looker Studio), ensure tight Marketing Agent (Insights skill) integration.

Our tech stack

Python, Go, Kafka, Databricks, Airflow, Flink (Java), GCP, Mongo, Redis, Airflow, DataProc, Spark, Apache Flink, Databricks, Kubernetes, Terraform, Grafana, Prometheus, PagerDuty, Sentry, OpenTelemetry, GitLab CI/CD, Claude Code

Your success story

30 Days: Understand the Datacraft domain, complete onboarding, set up your dev environment, and get oriented on Databricks architecture and Marketing Agent.

90 Days: Ship your first pipeline, data model, or orchestration improvement to production. Join architecture discussions and the on-call rotation.

180 Days: Own a component end-to-end. Make informed trade-off decisions independently. Contribute to measurable team goals.

You have the following experience and qualities:

Professional experience

• Solid data engineering background with strong SQL and data modeling skills (star/snowflake schemas, slowly changing dimensions, partitioning/clustering, etc.).
• Hands-on experience building production-grade data pipelines on Databricks and GCP, ideally involving Flink, Iceberg, Spark on DataProc.
• Experience with orchestration and workflow tools — specifically Airflow / Cloud Composer — and comfort working with DAG-based systems for scheduled and event-driven jobs.
• Familiarity with open table formats (Iceberg preferred, Delta Lake / Hudi acceptable) and how they interact with query engines and DWH platforms.
• Strong programming skills in Python (preferred); Scala/Java/Go also relevant.
• Good understanding of data quality, lineage, and observability (monitoring SLAs/SLOs, detecting missing/late loads, backfilling strategies).
• Ability to work across product and engineering teams, turning fuzzy problem statements into incremental, shippable slices.

Strongly preferred

• Background in marketing analytics, CDPs, or BI/semantic layers (Looker, dbt, Cube).
• Experience with Snowflake or Databricks or BigQuery.
• Experience with spec driven development, knowledge graphs, agentic harnesses or AI-powered analytics

Personal qualities

Ownership & accountability · Sharp and Product thinking · Clear communication · Bias for reliability · Continuous improvement mindset · Comfortable remote-first in Central Europe.

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