Senior Azure Databricks Engineer

Senior Data Engineer – Azure & Databricks (Cloud Data Platform)

We are building a modern, scalable cloud data platform to power analytics, reporting, and advanced data-driven decision-making across our organization. As a Senior Data Engineer, you will play a pivotal role in designing and operating this platform — leading architecture, implementing best practices, ensuring data quality and governance, and driving continuous improvement. Your work will directly impact how the organization leverages data to deliver value.

What You’ll Own — Key Responsibilities & Impact

• Implement and maintain large‑scale data pipelines and the Azure/Databricks data platform in close collaboration with the Architect, contributing to design discussions and proposals.

• Build robust, scalable pipelines using Azure Databricks (PySpark / SQL), integrating data ingestion, processing, transformation, and storage.

• Design and enforce data architecture standards: Delta Lake / Lakehouse architecture, data modeling (dimensional models, star/snowflake schemas), data warehousing or lakehouse solutions.

• Manage ingestion and orchestration using Azure Data Services — e.g., Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure Synapse Analytics, and related services for storage, compute, and analytics.

• Establish and enforce CI/CD pipelines for data workflows and infrastructure using Azure DevOps or equivalent tools, ensuring reliable, repeatable deployments and maintainability.

• Implement and uphold data governance, metadata management, and data quality practices — ensuring data integrity, consistency, and compliance across pipelines and systems.

• Monitor, troubleshoot, and optimize performance of data processing jobs (Spark/Databricks) — ensuring efficient, reliable, and performant data workflows even at scale.

• Collaborate with cross-functional teams — data analytics, product, business stakeholders, compliance — to understand requirements, deliver data solutions, and explain complex technical concepts clearly to non-technical audiences.

• Proactively research, evaluate, and adopt new data/cloud technologies and best practices; champion continuous improvement, scalability, and long-term reliability of the data platform.

Who You Are — Required & Preferred Qualifications

• 5+ years of experience as a data engineer (or similar), with significant exposure to cloud-based data platforms and modern data architectures.

• Proven hands-on experience building and managing data pipelines using Azure Databricks (PySpark + SQL) in real-world production environments.

• Strong understanding and practical experience with data modeling, data warehousing / lakehouse architecture (e.g. dimensional modeling, star/snowflake schemas, Delta Lake / Lakehouse).

• Proven track record in data governance, metadata management, and ensuring data quality at scale.

• Solid experience in performance optimization and troubleshooting of data processing jobs / pipelines (Spark/Databricks).

• Excellent programming and query skills — strong SQL, Python (or another relevant language); ability to write clean, efficient, maintainable code.

• Strong analytical and problem-solving skills; ability to think at both micro (pipeline/job level) and macro (architecture/strategy) levels.

• Excellent communication skills: able to explain complex technical issues to non-technical stakeholders, collaborate across teams, and influence architectural decisions.

• Self-motivated, responsible, and capable of working independently and as a technical leader in a structured data platform environment.

Preferred / Nice to Have:

• Prior experience working in regulated domains or sectors with strong compliance requirements (e.g. Finance, Asset Management, Pensions).

• Previous involvement in platform modernization or cloud migration projects.

• Familiarity with additional big data / data-engineering tools and patterns beyond Spark / Databricks — streaming, real-time data ingestion, advanced orchestration, metadata tooling, monitoring & alerting.

• Experience mentoring or leading smaller data engineering teams / peers; championing best practices, code reviews, architecture governance.

• Familiarity with CI/CD for data workflows, preferably with Azure DevOps (or similar), including infrastructure-as-code (Terraform / ARM templates).

• Experience with Azure Data Services such as ADF, ADLS, Synapse (or comparable cloud data services).

• Employ infrastructure-as-code (e.g. Terraform or ARM templates) to provision, manage, and version cloud infrastructure and data platform resources.

What we offer for you

• Participation in full-cycle and diverse international projects

• Opportunity to work as a specialist or manager/team lead

• Constant career development with internal mentorship

• Access to a whole set of learning platforms, paid certifications

• Flexible working conditions, home working is allowed

• Attractive base salary & Wide range of benefits included cafeteria, bonuses, private health insurance package, life insurance, AYCM sport card, referral bonus, family-oriented benefits, company shares on a discount price

Budapest

平等就业机会声明

所有聘用决定均不考虑年龄、种族、信仰、肤色、宗教、性别、国籍、血统、残疾状况、退伍军人身份、性取向、性别认同或表达、基因信息、婚姻状况、公民身份或任何其他受联邦、州或地方法律保护的因素。

求职者在招聘过程中没有义务披露已封存或已删除的定罪或逮捕记录。

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请阅读埃森哲的招聘和聘用声明，了解更多关于我们在招聘和聘用过程中如何处理您的数据的信息。

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