Senior Data Engineer

 Posted 16 hours ago
     
2-5 years experience
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AI Summary

Design and operate data models and transformation pipelines to build a Realtime Data Platform. Collaborate with stakeholders to deliver trusted insights through KPIs, dashboards, and semantic layers.

We’re building a Realtime Data Platform – a platform that ingests data from multiple external sources, normalizes it into canonical models, and serves it for analytics, dashboards, and client-facing reports.

As a BI Data Engineer, you’ll design and operate data models and transformation pipelines, ensure data quality and reliability for decision-making, and collaborate with analysts and business stakeholders to deliver trusted insights.

Responsibilities

 

Data Ingestion & Transformation

Design and maintain ingestion & transformation flows (dbt, SQL, Python).

Build reliable pipelines from ETLs, CDC, APIs, CSVs, and event streams into analytical models.

Ensure deduplication and data integrity for BI reporting.

 

Data Modeling & Warehousing

Develop semantic and analytical models (fact/dimension tables, star/snowflake schemas).

Optimize query performance in BI warehouse (currently Athena with Iceberg but in the future maybe ClickHouse, Redshift, BigQuery or Starrocks).

Implement versioned entities and audit trails for business data.

 

Analytics Enablement

Build pre-aggregations and semantic layers (Cube, dbt metrics and models).

Support dashboards and client-facing reports in Grafana.

Design KPIs and metrics with product, risk, and operations teams.

 

Data Quality & Observability

Implement validation checks (dbt tests, Pydantic).

Monitor data freshness, pipeline SLAs, and dashboard accuracy.

Set up alerts and documentation for business users.

 

Collaboration & Stakeholder Support

Work closely with analysts, product managers, and operations to understand BI needs.

Expose data via APIs/semantic layers for self-service exploration.

Contribute to the design of rules for reporting policies and metric definitions.

 

Requirements

Experience: 3+ years in BI engineering, data engineering, or analytics engineering.

Data Warehouses: strong SQL skills, experience with at least one warehouse (Athena, Redshift, ClickHouse, Snowflake, BigQuery).

Modeling: hands-on with dimensional modeling, dbt, star/snowflake schemas, metric layers.

Programming: Python for transformations .

Data Quality: experience with validation, deduplication, audit logs.

CI/CD & Infra: GitHub Actions or similar, Terraform/CDK basics, containerized pipelines.

Mindset: detail-oriented, reliable, collaborative with business users.

 

Nice to Have

Knowledge of semantic layers (Cube, dbt metrics).

Experience with AWS and cloud Infrastructure.

Experience with client-facing dashboards.

Experience with Grafana or another BI visualization tool.

Familiarity with real-time analytics and pre-aggregations.

Esports fan.

 

What We Offer

Opportunity to shape the BI architecture from the ground up.

Modern realtime analytics stack (dbt, Cube, Grafana, Postgres, Iceberg).

Collaborative, engineering-led environment with strong focus on analytics.

Experience immense potential for personal growth while contributing to an innovative team.

Work remotely or in a hybrid style – whatever suits you best.

Enjoy our luxurious Norse-myth-inspired offices in Prague.

Improve your English with company-sponsored language courses.

Participate in quarterly team-building activities to bond with your team.

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