Staff Data Engineer - Enterprise Platform, AI foundations
About this role
The daily work centers on building, scaling, and modernizing an enterprise data platform to support executive reporting, revenue operations, and AI-ready data foundations at petabytes scale. Team members develop, maintain, and troubleshoot production-grade data pipelines while partnering closely with analytics, product, finance, and GTM stakeholders. This position exists to strengthen data governance, observability, and operational reliability across complex business domains like Salesforce and billing.
Ideal candidates are relentlessly curious problem-solvers who enjoy tackling hard technical challenges in an AI-enabled enterprise environment. A successful engineer in this group actively seeks out new solutions, experiments thoughtfully, and collaborates well across both technical and business teams. Someone who thrives on platform ownership and wants high visibility across global enterprise operations will find a strong fit here.
What you will do
- Build, maintain, and troubleshoot production-grade data pipelines across source systems, cloud data platforms, and business-facing data products dealing with petabytes of data.
- Support and improve critical data workflows across Salesforce, billing, ARR, customer data, and finance domains using various integration and visualization tools.
- Improve data quality, observability, freshness monitoring, schema validation, reconciliation, alerting, and operational reliability for critical datasets.
- Participate in production support for business-critical data workflows, including incident response, root-cause analysis, and runbook development.
- Strengthen data governance and discoverability through metadata management, lineage, ownership, certification, and metric definitions.
- Partner with Analytics, BI, Product, Finance, GTM, IT, Security, and Engineering stakeholders to deliver trusted datasets and scalable data solutions.
- Leverage AI tools responsibly to increase engineering productivity, including SQL support, Python development, debugging, testing, and operational analysis.
What you need
- Demonstrate advanced SQL and Python proficiency for building, optimizing, troubleshooting, automating, and testing data pipelines across large datasets.
- Bring proven experience building and supporting batch or near-real-time ingestion pipelines using tools like Nexla, Workato, Fivetran, APIs, or custom pipelines.
- Possess hands-on experience with cloud-based data stacks such as GCP and BigQuery or comparable AWS alternatives including production dataset management and performance tuning.
- Have experience with workflow orchestration tools such as Kestra, Airflow, or dbt Cloud, covering scheduling, dependencies, retries, and failure handling.
- Maintain a deep understanding of dimensional modeling principles and data quality and reliability practices like reconciliation, schema validation, and freshness monitoring.
- Show familiarity with metadata management, lineage, data catalogs, semantic layers, and standard engineering best practices including Git, CI/CD, testing, and code reviews.
Benefits
- Restricted Stock Units (RSUs) and Employee Stock Purchase Plan (ESPP)
- Flexible time off on top of standard 5 weeks PTO, paid wellness days, and fully paid short-term sick/nursing leave
- Private medical care benefit, life and disability insurance, and pension insurance contribution
- Global home office allowance, meal allowance, and hybrid work options
- Wellbeing allowance, MultiSport benefit program, and Wellness Coach app
Skills and tech stack
Questions candidates ask
What is the remote work and office policy for this role?
The position offers hybrid work in Prague (Karlin), Brno (Clubco) or remote in CZ/SK. Only Prague-based employees are required to work from the office at least 2 days per week.
What core tools and cloud platforms will I be using?
You will work with BigQuery, GCP, Kestra, Nexla, DataHub, Looker, Tableau, and Workato across Salesforce, billing, ARR, customer data, and finance domains. The role requires advanced SQL and Python proficiency along with cloud-based data stack experience.
Who will I be collaborating with across the company?
You will partner with Analytics, BI, Product, Finance, GTM, IT, Security, and Engineering stakeholders to deliver trusted datasets, AI-ready data foundations, and scalable data solutions.