Data Engineering Technical Supervisor (Medior) – Databricks & Python

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Cég neve

Thermo Services (Hungary) Kft.
Munkavégzés helye

Budapest
Profession Prémium

Nézd meg, mennyire felelsz meg ennek az állásnak. Mennyire passzolok?

Munkaidő, foglalkoztatás jellege
- Alkalmazotti jogviszony
- Általános munkarend
Elvárt technológiák
- PYTHON SQL AWS AZURE TESTING SECURITY SPARK GIT APACHE BI TROUBLESHOOTING
Elvárások
- Angol középfok
- 3-5 év tapasztalat
- Főiskola

Állás elmentve

A hirdetést eltávolítottuk a mentett állásai közül.

Responsibilities

Technical leadership and mentoring of data engineers
Technical oversight for Databricks solutions
Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake
Guidance on architecture, design patterns, coding standards, testing, and performance optimization
Review of technical designs and code for scalability, maintainability, security, and alignment with engineering standards
Troubleshooting complex production issues and root-cause analysis
Reduction of technical debt and improvement of platform reliability
Promotion of engineering best practices including Git-based source control, automated testing, CI/CD, peer review, and documentation
Development of reusable Python/PySpark components and standardized patterns for data ingestion, transformation, validation, and processing
Work with Delta Lake, Unity Catalog, and lakehouse architecture patterns
Support of Databricks workflow orchestration and automation
Implementation of data quality, monitoring, observability, and error-handling mechanisms
Enablement of BI developers to build ETL/ELT pipelines within governed engineering patterns
Facilitation of technical discussions, design reviews, knowledge sharing, and technical onboarding
Fostering a collaborative engineering culture focused on ownership, continuous improvement, and high-quality delivery
Partnership with BI developers, analysts, product owners, and business stakeholders to translate data requirements into scalable technical solutions
Provision of technical estimates, identification of dependencies and risks, and support of prioritization and delivery of engineering initiatives
Communication of technical concepts, trade-offs, risks, and recommendations to technical and non-technical stakeholders
Ensuring solutions meet functional, performance, security, quality, and operational requirements

Requirements

Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related discipline, or equivalent professional experience
4+ years of professional experience in data engineering, software engineering, or a related technical field
Strong hands-on experience with Python/PySpark, Databricks, Apache Spark, and SQL in production data engineering
Experience designing and operating production-grade ETL/ELT pipelines using Delta Lake and lakehouse architecture concepts
Solid understanding of data modeling, data quality, partitioning, performance optimization, and distributed data processing
Experience with Git-based development, automated testing, CI/CD, and code review
Demonstrated ability to troubleshoot complex technical issues and provide constructive engineering guidance
Experience mentoring engineers or providing technical leadership
Strong analytical, problem-solving, communication, and stakeholder-management skills

Nice-to-have

Experience with Databricks on AWS/GCP/Azure
Experience with Unity Catalog and Databricks governance capabilities
Experience with data observability, monitoring, and pipeline automation
Experience optimizing Spark/Databricks workloads for performance and cost

Company info

Thermo Fisher Scientific Inc. is the world leader in serving science, with annual revenue of more than $40 billion. Our global team delivers an unrivaled combination of innovative technologies, purchasing convenience and pharmaceutical services through our industry-leading brands, including Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific, Unity Lab Services, Patheon and PPD.