Senior Databricks Engineer | Bulgaria

At Deloitte, the role involves designing and delivering modern cloud-based data platforms that power business-critical insights, advanced analytics, and AI-driven solutions. The position focuses on building scalable Lakehouse solutions using the latest Databricks technologies and working alongside Data Architects, Data Scientists, AI specialists, and business leaders on international projects across industries.

• 5+ years of experience in Data Engineering.
• Strong hands-on experience with Databricks and Apache Spark.
• Advanced knowledge of PySpark, Python, and SQL.
• Proven experience designing and implementing production-grade ETL/ELT solutions.
• Experience building modern data platforms and Lakehouse architectures.
• Strong understanding of Delta Lake, data modelling, and distributed data processing.
• Experience with batch and streaming data pipelines.
• Strong knowledge of Spark optimization and performance tuning.
• Experience working with Azure, AWS, or GCP.
• Familiarity with Git, CI/CD, testing, and modern software engineering practices.
• Strong communication and stakeholder management skills.
• Ability to lead technical initiatives and drive projects independently from design through production.
• Experience mentoring or guiding other engineers.
• Excellent English language skills and native Bulgarian.

Nice to have:

• Experience with Unity Catalog.
• Experience with Databricks Asset Bundles.
• Experience with Lakeflow.
• Experience with Auto Loader.
• Experience with Structured Streaming.
• Experience with Terraform.
• Experience with dbt.
• Experience with MLflow.
• Databricks Data Engineer Professional Certification.

• Lead the design and delivery of end-to-end Data Engineering solutions on the Databricks platform.
• Take ownership of projects from requirements gathering and solution design through deployment and production support.
• Design and build scalable data pipelines using Databricks, PySpark, Python, and SQL.
• Develop modern Lakehouse architectures using Delta Lake and Medallion Architecture principles.
• Deliver batch, incremental, and streaming data processing solutions.
• Partner with Data Architects, Data Scientists, and business stakeholders to translate complex requirements into scalable technical solutions.
• Define engineering standards, reusable frameworks, and development best practices.
• Optimize Spark workloads for performance, scalability, reliability, and cost efficiency.
• Implement data governance and security controls using Unity Catalog.
• Lead code reviews, technical workshops, and architecture discussions.
• Drive CI/CD, automation, testing, and deployment best practices.
• Troubleshoot and resolve complex production and performance challenges.
• Mentor and support Data Engineers, fostering technical excellence and continuous learning.