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# Senior Data Engineer, Datacraft team

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/bloomreach.md)ShareRemote from[Czechia](https://jobicy.com/job-region/czechia.md)SalaryCZK 1,300k–1,600k / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished26 Oct 2026Apply before25 Nov 2026Listing views55Application actions4Application toolkit

## Make your next move.

Prepare your resume, explore your fit, and draft a cover letter for this opportunity.

AI Summary

## The role, at a glance.

Bloomreach is seeking a senior data engineer to help found its Datacraft team and build a next-generation data platform for customer data sharing, analytics, and AI-powered marketing insights. The role centers on production data pipelines across Kafka, Flink, GCS Iceberg, Databricks, Spark, and GCP, with responsibility for data modeling, orchestration, observability, and consent semantics. The engineer will also contribute to canonical metrics, semantic layers, dashboards, and integrations with the Marketing Agent. This is a senior, high-ownership position requiring independent delivery, architectural judgment, and fluent use of AI coding tools in a remote-first Central European environment.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

4/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

4/5IndependentCollaborative

AI insightThe role requires deep hands-on expertise across distributed streaming, lakehouse architecture, data modeling, cloud infrastructure, and operational reliability. As a founding senior engineer, the hire is expected to turn ambiguous objectives into production systems with minimal day-to-day guidance.

## Salary analysis

Estimated compensation compared with the broader CZK market for similar roles.

Estimated job median (per year)Market rateCZK1,450,000CZK market range (per year)CZK1,300k–CZK1,800k0CZK1,980.00k

AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a base salary range of CZK 1,300,000–1,600,000 per year; the annual cadence is inferred from the senior full-time engineering context and the stated CZK amount. The midpoint is CZK 1,450,000 annually. An estimated market range for a senior data engineer in Czechia with Databricks, GCP, streaming, and platform ownership experience is CZK 1,300,000–1,800,000 annually.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Data engineering](https://jobicy.com/jobs?search_keywords=Data%20engineering.md)[Databricks](https://jobicy.com/jobs?search_keywords=Databricks.md)[Google Cloud Platform](https://jobicy.com/jobs?search_keywords=Google%20Cloud%20Platform.md)[Apache Spark](https://jobicy.com/jobs?search_keywords=Apache%20Spark.md)[Apache Flink](https://jobicy.com/jobs?search_keywords=Apache%20Flink.md)[Apache Kafka](https://jobicy.com/jobs?search_keywords=Apache%20Kafka.md)[Apache Iceberg](https://jobicy.com/jobs?search_keywords=Apache%20Iceberg.md)[Apache Airflow](https://jobicy.com/jobs?search_keywords=Apache%20Airflow.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Data modeling](https://jobicy.com/jobs?search_keywords=Data%20modeling.md)[ETL pipelines](https://jobicy.com/jobs?search_keywords=ETL%20pipelines.md)[Data observability](https://jobicy.com/jobs?search_keywords=Data%20observability.md)[Terraform](https://jobicy.com/jobs?search_keywords=Terraform.md)[Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md)

Sample interview questionsHow would you design a pipeline from Kafka through Flink and Iceberg into Databricks while ensuring reliable processing?I would define event schemas and compatibility rules first, then use Flink checkpoints and idempotent writes to provide reliable processing. Data would land in partitioned Iceberg tables on GCS with clear bronze, silver, and gold layers, while Databricks jobs would validate quality, publish curated models, and expose operational metrics for freshness, volume, failures, and lag.

How do you model identity resolution and consent semantics in an analytics platform?

I would maintain canonical entity identifiers with explicit source provenance, effective timestamps, and survivorship rules. Consent should be modeled as a time-aware, purpose-specific policy layer so downstream datasets and dashboards can reliably enforce the correct eligibility at query and activation time.

What approach would you take to data quality and late-arriving events?

I would establish measurable data contracts and SLAs for completeness, freshness, uniqueness, and schema validity. For late data, I would use watermarking where appropriate, retain replayable raw data, support partition-level backfills, and publish clear observability signals so consumers understand revisions to metrics.

Describe how you would convert a vague stakeholder request for a new dashboard into an incremental delivery plan.

I would clarify the business decision, intended users, metric definitions, grain, data sources, and acceptable freshness. I would then deliver a narrow first version with documented canonical metrics and validation against existing reports, followed by iterative enhancements to the semantic layer, dashboard experience, and data reliability.

How do you use AI coding agents responsibly in production data engineering work?

I use them to accelerate exploration, boilerplate generation, test creation, documentation, and code review preparation, while retaining ownership of design and validation. Generated changes must pass normal engineering controls, including peer review, security checks, test coverage, data-quality validation, and production monitoring.

Opportunity details

## About this role.

Bloomreach is building the world’s premier agentic platform for personalization.We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey.

* We’re taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses.
* We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey.
* We’re designing the future of autonomous marketing, taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do.

And we’re building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn’t only autonomous…it’s also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora.

### 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.

#LI-KP1

### More things you’ll like about Bloomreach:

### Culture:

*

A great deal of freedom and trust. At Bloomreach we don’t clock in and out, and we have neither corporate rules nor long approval processes. This freedom goes hand in hand with responsibility. We are interested in results from day one.

*

We have defined our [5 values](https://www.bloomreach.com/en/careers?utm_source=Job-Description-Footer&utm_medium=Job-Description&utm_content=Hyperlink-1) and the 10 underlying key behaviors that we strongly believe in. We can only succeed if everyone lives these behaviors day to day. We’ve embedded them in our processes like recruitment, onboarding, feedback, personal development, performance review and internal communication.

*

We believe in flexible working hours to accommodate your working style.

*

We work virtual-first with several Bloomreach Hubs available across three continents.

*

We organize company events to experience the global spirit of the company and get excited about what’s ahead.

*

We encourage and support our employees to engage in volunteering activities – every Bloomreacher can take 5 paid days off to volunteer*.

*

The [Bloomreach Glassdoor page](https://www.glassdoor.com/Overview/Working-at-Bloomreach-EI_IE442167.11,21.htm) elaborates on our stellar 4.7/5 rating. The [Bloomreach Comparably page](https://www.comparably.com/companies/bloomreach) Culture score is even higher at 4.9/5

### Personal Development:

*

We have a People Development Program – participating in personal development workshops on various topics run by experts from inside the company. We are continuously developing & updating competency maps for select functions.

*

Our resident communication coach [Ivo Večeřa](https://www.linkedin.com/in/ivo-ve%C4%8De%C5%99a-2a94291/) is available to help navigate work-related communications & decision-making challenges.*

*

Our managers are strongly encouraged to participate in the Leader Development Program to develop in the areas we consider essential for any leader. The program includes regular comprehensive feedback, consultations with a coach and follow-up check-ins.

*

Bloomreachers utilize the $1,500 professional education budget on an annual basis to purchase education products (books, courses, certifications, etc.)*

### Well-being:

*

The Employee Assistance Program — with counselors — is available for non-work-related challenges.*

*

Subscription to Calm – sleep and meditation app.*

*

We organize ‘DisConnect’ days where Bloomreachers globally enjoy one additional day off each quarter, allowing us to unwind together and focus on activities away from the screen with our loved ones.

*

We facilitate sports, yoga, and meditation opportunities for each other.

*

Extended parental leave up to 26 calendar weeks for Primary Caregivers.*

### Compensation:

*

Restricted Stock Units or Stock Options are granted depending on a team member’s role, seniority, and location.*

*

Everyone gets to participate in the company’s success through the company performance bonus.*

*

We offer an employee referral bonus of up to $3,000!

*

We reward & celebrate work anniversaries — Bloomversaries!*

(*Subject to employment type. Interns are exempt from marked benefits, usually for the first 6 months.)

Excited? Join us and transform the future of commerce experiences!

If this position doesn’t suit you, but you know someone who might be a great fit, share it – we will be very grateful!

Any unsolicited resumes/candidate profiles submitted through our website or to personal email accounts of employees of Bloomreach are considered property of Bloomreach and are not subject to payment of agency fees.

#LI-Remote

Show more

[Apply now >](https://jobicy.com/jobs/157270-senior-data-engineer-datacraft-team.md)

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