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

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