Databricks Data Engineer

Stack

Responsibilities

• ▹Design, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• ▹Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality
• ▹Implement data governance and secure data access layers utilizing Databricks Unity Catalog
• ▹Write clean, efficient, and maintainable SQL and Python code within Databricks Notebooks and IDEs
• ▹Develop automation scripts leveraging the Databricks CLI and REST APIs to manage workspace assets and configurations
• ▹Establish, maintain, and optimize CI/CD pipelines (e.g., GitHub Actions, GitLab CI/CD) leveraging Declarative Automation Bundles (DABs) as the primary mechanism for rapid, reliable, software-defined project deployments
• ▹Automate and orchestrate data pipeline processes using Databricks Workflows or Spark Declarative Pipelines (formerly DLT)
• ▹Deliver solutions centered on the Databricks ecosystem, integrating seamlessly with cloud-native storage and security services (e.g., AWS S3/IAM, Azure ADLS/Entra ID, or Google Cloud Storage/IAM)
• ▹Design and implement modern data modeling and data warehousing solutions using Databricks SQL Warehouses
• ▹Own and manage the technical aspects of deliveries (at least at component level)
• ▹Participate in project planning, task estimation, testing, and liaising with business stakeholders
• ▹Create comprehensive technical documentation

Requirements

• ▹Proficiency in both SQL and Python, emphasizing clean, efficient, and maintainable code optimized for cloud data platforms
• ▹Hands-on experience utilizing AI coding tools and agents (e.g., Databricks Assistant in Chat/Agent mode, GitHub Copilot, Cursor, or Claude Code) to augment programming workflows, generate boilerplate code, and resolve errors
• ▹Experience with API integration and scripting for platform automation
• ▹Hands-on experience using Declarative Automation Bundles (DABs) to manage, bundle, and deploy Databricks resources as code
• ▹Solid understanding of standard CI/CD tools (e.g., GitHub Actions, GitLab CI/CD) and version control (Git/Databricks Repos) to streamline development lifecycles
• ▹3-5 years of hands-on experience in data engineering, with a strong focus on Databricks Lakehouse architecture
• ▹Proven track record of delivering at least one complex, scalable data solution utilizing core Databricks features (Unity Catalog, Delta Lake, Databricks SQL)
• ▹Strong experience operating Databricks within at least one major cloud environment (AWS, Azure, or GCP)
• ▹Native Hungarian and excellent written and verbal communication skills in English

Nice to have

• ▹Experience working with dbt (specifically dbt-databricks)
• ▹Knowledge of Databricks AI/ML and GenAI capabilities (e.g., Mosaic AI, Databricks Assistant/Genie, MLflow, Feature Store, or Model Serving)
• ▹Apache Spark knowledge

Soft skills

What we offer

• ▹Diverse projects - in each assignment there is always something new, either on the technical or the business side, that helps you grow
• ▹Empowerment - trust is a cornerstone of the culture; they'll hold your hand if you need it, but give you space to push your limits
• ▹Flexible ways of working - the office on Bartók Béla Road is also a community space, and people work when and how they work best
• ▹Balanced life - a healthy work/life balance is considered essential, without pointless meetings and unnecessary administration
• ▹Mentoring from your first day, with continuous support throughout your career path
• ▹Learning & development opportunities
• ▹Supportive corporate culture based on comradery, mutual support, and respect

About the company

Hiflylabs is a Budapest-based company with 250+ employees, where the application development team and business intelligence experts work to provide effective solutions to business problems. With 10 years of experience across Hungarian and international Business Intelligence projects in sectors like finance, telecom, and energy, they deliver a wide portfolio including Data Warehouses, Business Intelligence, and Data Analytics.