What you bring:
- 3-5 max years of experience in Data Engineering.
- Hands-on experience with Databricks and Apache Spark.
- Strong skills in PySpark, Python, and SQL.
- Experience developing production-grade ETL/ELT pipelines.
- Good understanding of Delta Lake, Lakehouse Architecture, and data modelling.
- Experience with batch and incremental data processing.
- Understanding of Spark optimization and distributed data processing concepts.
- Experience with Azure, AWS, or GCP.
- Familiarity with Git and modern software engineering practices.
- Strong analytical and problem-solving skills.
- Ability to independently deliver Data Engineering solutions from development to production.
- Excelleng English language skills and native Bulgarian are a must
- Nice to have
- Unity Catalog
- Databricks Asset Bundles
- Auto Loader
- Structured Streaming
- Lakeflow
- Terraform
- dbt
- CI/CD experience
- Databricks Certification
At Deloitte, we help organizations unlock the value of their data through modern cloud platforms, advanced analytics, and AI-driven solutions. As a Databricks Data Engineer, you will design, build, and optimize scalable data solutions that power critical business insights and future AI initiatives.
You will work alongside Data Architects, Data Scientists, and experienced Data Engineers to deliver enterprise-grade Lakehouse solutions using Databricks and modern cloud technologies. This role is ideal for someone who enjoys solving complex data challenges, building scalable platforms, and taking ownership of solutions from development through production.
What we offer:
Why Deloitte
- Work on Data & AI projects
- Build modern data platforms that enable analytics, machine learning, and AI.
- Grow your Databricks expertise
- Work with the latest Databricks technologies, cloud platforms, and engineering best practices.
- Learn from experienced specialists
- Collaborate with Architects, Engineers, and Data Scientists across Deloitte's international network.
- Develop your career
- Access certifications, continuous learning opportunities, mentorship, and clear growth paths.
- Work across industries
- Support leading organizations across Financial Services, Retail, Consumer, Energy, Manufacturing, Telecommunications, and Public Sector.
,[Design and build scalable ETL/ELT data pipelines using Databricks, PySpark, Python, and SQL., Develop modern Lakehouse solutions using Delta Lake and Medallion Architecture., Build batch, incremental, and streaming data processing solutions., Optimize Spark workloads for performance, scalability, reliability, and cost efficiency., Implement data quality, monitoring, troubleshooting, and operational best practices., Configure and manage Databricks Workflows and Jobs., Support data governance and access controls using Unity Catalog., Collaborate with Architects, Data Scientists, and business stakeholders to deliver high-quality solutions., Contribute to code reviews, CI/CD processes, and engineering best practices., Troubleshoot production issues and continuously improve platform performance and reliability] Requirements: Cloud platform, Databricks, AI, Cloud, Data engineering, Spark, PySpark, Python, SQL, ETL, Data modelling, Azure, AWS, GCP, Git, UNITY, Terraform, dbt, CD