At LeverX, we have had the privilege of delivering over 1,500 projects for various clients. With 20+ years in the market, our team of 2,200 is strong, reliable, and always evolving: learning, growing, and striving for excellence.
We are looking for a Databricks Engineer to join us. Let’s see if we are a good fit for each other!
what we offer:
- Projects in different domains: healthcare, manufacturing, e-commerce, fintech, etc.
- Projects for every taste: Startup products, enterprise solutions, research & development initiatives, and projects at the crossroads of SAP and the latest web technologies.
- Global clients based in Europe and the US, including Fortune 500 companies.
- Employment security: We hire for our team, not just for a specific project. If your project ends, we will find you a new one.
- Healthy work atmosphere: On average, our employees stay with the company for 4+ years.
- Market-based compensation and regular performance reviews.
- Internal expert communities and courses.
- Perks to support your growth and well-being.
required skills:
- 3+ years of professional Data Engineering experience.
- Strong hands-on experience with Databricks, dbt (Data Build Tool), SQL, and Python and/or PySpark.
- Good understanding of Delta Lake, lakehouse architecture, and distributed data processing.
- Experience designing and maintaining production-grade ELT pipelines.
- Experience with Git and CI/CD development workflows.
- Understanding of data modeling, data quality, testing, and data governance concepts.
- Experience working with at least one major cloud platform: Azure, AWS, or GCP.
- Strong troubleshooting and performance optimization skills.
- English B2+.
nice-to-have skills:
- Databricks certifications.
- Experience with Databricks Unity Catalog.
- Experience with orchestration tools such as Databricks Workflows, Airflow, or Azure Data Factory.
- Experience with Infrastructure as Code, particularly Terraform.
- Knowledge of dimensional modeling and modern analytics engineering practices.
- Experience working with large-scale enterprise data platforms.
responsibilities:
- Design, develop, and maintain scalable data pipelines and transformation workflows using Databricks and dbt.
- Build reliable ETL/ELT processes for structured and semi-structured data using SQL, Python, and PySpark.
- Implement and optimize Delta Lake tables and lakehouse architectures for performance, scalability, and cost efficiency.
- Develop reusable, tested, and well-documented dbt models, including automated data quality checks and monitoring.
- Collaborate with data analysts, data scientists, software engineers, and business stakeholders to translate requirements into robust data solutions.
- Support CI/CD, version control, and automated testing practices for data pipelines and transformation workflows.
- Troubleshoot production data issues, optimize Databricks workloads, and continuously improve data platform reliability and observability.