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Senior data engineer (databricks focused)

London
BDO
Data engineer
Posted: 27 April
Offer description

Putting people first, every day


BDO is a firm built on a foundation of positive relationships with our people and our clients. Each day, our professionals provide exceptional service, helping clients with advice and insight they can trust. In turn, we offer an award-winning environment that fosters a with a high priority on your personal and professional growth.

Your Opportunity

BDO Digital is seeking an experienced and technically proficient Senior Data Engineer (Databricks Focused) to join our Technology Advisory Services practice. This net new role blends technical leadership with hands-on data engineering, focusing on delivering scalable, secure, and production-grade data pipelines using Azure and Databricks. The successful candidate will also lead client engagements, aligning data initiatives with business objectives to create real-world impact.

Key Responsibilities
Data Engineering and Platform Development

1. Design, build, and optimize robust data pipelines using Databricks, Delta Lake, and Apache Spark.
2. Develop scalable ETL processes for structured and unstructured data, ensuring data quality and reliability.
3. Implement data integration solutions across cloud and on-premises sources, leveraging Databricks and Azure Data Lake.
4. Automate data ingestion, transformation, and validation workflows.
5. Monitor, troubleshoot, and enhance data pipeline performance and reliability.
6. Ensure compliance, security, and operational excellence across all data workflows.

Client and Team Leadership

7. Serve as a primary technical lead for client engagements focused on data engineering and analytics solution delivery.
8. Translate business requirements into scalable data architectures and operational plans.
9. Collaborate with cross-functional teams to integrate data solutions into production environments.
10. Mentor junior team members and promote adoption of best practices in data engineering and cloud analytics.

Data Application

11. Convert business requirements and analytics prototypes into robust, scalable data solutions.
12. Apply appropriate data modeling and transformation techniques to support analytics and machine learning initiatives.
13. Document data pipelines and contribute to internal knowledge sharing.

Qualifications
Required

14. Educational Background: A Bachelor’s or master’s degree in Computer Science, Data Engineering, Information Systems, or a closely related discipline. Strong foundation in data structures, algorithms, and distributed systems.
15. Professional Experience: A minimum of 5 years of hands-on experience in data engineering, including at least 3 years of direct experience with Databricks, Apache Spark, and cloud data platforms. Proven success in deploying and maintaining large-scale data solutions in production environments.
16. In-depth knowledge of the Microsoft Azure ecosystem, with demonstrated experience using services such as Azure Data Lake, Azure Databricks, Azure Synapse, and Azure DevOps.
17. Very strong proficiency with Databricks, including hands-on work with Delta Lake, Apache Spark, and data pipeline orchestration. Experience optimizing performance and reliability in production.
18. Advanced programming skills in Python and/or Scala, with practical experience using data engineering libraries and frameworks.
19. Solid understanding of CI/CD practices, with experience designing and maintaining pipelines using tools like GitHub Actions, Azure DevOps, or Jenkins. Familiarity with infrastructure-as-code tools such as Terraform or ARM templates for automating environment provisioning and deployment.
20. Excellent written and verbal communication skills, with the ability to effectively engage with a range of stakeholders, including data scientists, engineers, business partners, and executive leadership. Proven ability to explain technical concepts to non-technical audiences and influence decision-making.

Preferred

21. Certifications: Professional certifications such as Databricks Certified Data Engineer or Microsoft Certified, e.g. Azure Data Engineer Associate.
22. Experience with data governance, data security, and compliance frameworks.
23. Consulting experience and excellent communication and client management skills.

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