3 days ago
Bucharest, RomaniaSenior
Responsibilities
- Design, build, secure, maintain, and optimize scalable end-to-end data pipelines using ETL/ELT patterns.
- Configure and optimize Databricks clusters, manage Delta Lake and Unity Catalog, and execute large-scale Apache Spark workloads.
- Develop high-performance data processing and data engineering workflows in Python.
- Ingest heterogeneous data sources and produce curated, analytics-ready data formats.
- Implement DataOps and DevOps practices including CI/CD, automated testing, Git version control, and deployment automation.
- Apply clean code, modular architecture, code reviews, testing frameworks, lifecycle management, and spec-driven development.
- Maintain operational data platforms and pipelines with security compliance, resilience, and horizontal scalability.
- Monitor pipeline performance, manage alerts and root-cause incidents, and optimize compute and storage costs through FinOps practices.
- Ensure data relevance, completeness, and consistency through automated validation, cleansing, and quality tracking.
- Recommend and deploy data technologies and architectures for data consumption, data modeling, interoperability, and middleware use cases.
- Establish operational frameworks and produce technical, architectural, and runbook documentation.
- Collaborate with business, technical, and international teams in English.
- Use AI agents, code assistants, and generative automation to improve engineering productivity.
Requirements
- In-depth Databricks expertise, including cluster configuration and optimization, Delta Lake, Unity Catalog, and large-scale Spark workloads.
- Strong proven experience with enterprise cloud environments, specifically Microsoft Azure services such as ADF, AZF, and ADLS, or AWS.
- Advanced proficiency in Python for high-performance data processing, algorithmic optimization, and data engineering workflows.
- Experience designing and building scalable ETL/ELT pipelines from heterogeneous data sources.
- Knowledge and practical application of DataOps, DevOps, CI/CD, automated testing, Git, and deployment automation.
- Strong knowledge of software development methodologies, including clean code, modular architecture, code reviews, testing frameworks, and lifecycle management.
- Hands-on experience with spec-driven development, contract testability, and deterministic delivery.
- Experience with operational maintenance, security compliance, resilience, scalability, monitoring, alerting, incident management, data quality, and FinOps optimization.
- Fluent spoken and written English is mandatory.
- Knowledge of JIRA and Confluence is preferred.
- Cloud or Databricks certifications are preferred.
- Knowledge of data modeling best practices is preferred.
- Experience with data visualization tools is preferred.
Benefits
- 24 holiday days per year.
- Benefit Online.
- Flexible working hours and a stated commitment to work-life balance.
- Comprehensive compensation and benefits package including medical coverage and life insurance.
- Hybrid workplace.
- Personal development opportunities and opportunities to move across domains, products, customers, countries, and Thales entities.
- Choice between a technical expertise path and a leadership path.
- Opportunities for an international career within Thales.
Tech Stack
Categories
Data Engineering
About Thales
Thales designs and sells defense, aerospace, space, and digital identity/cybersecurity systems to governments, armed forces, infrastructure operators, and enterprises. Its portfolio spans avionics, radars and sensors, satellites, air traffic management, secure communications, and cybersecurity and identity solutions (bolstered by the 2019 Gemalto acquisition). Headquartered in Meudon, France, Thales is publicly traded on Euronext Paris (HO) and reported €20.6 billion in sales in 2024.