Description
Project Description
We are looking for an experienced Data Engineer with deep expertise in Databricks to join our advanced analytics and data engineering team. The ideal candidate will play a key role in designing, building, and optimizing large-scale data solutions on the Databricks platform, supporting business intelligence, advanced analytics, and machine learning initiatives. You will collaborate with cross-functional teams to deliver robust, scalable, and high-performance data pipelines and architectures.
Technologies
- Databricks (including Spark, Delta Lake, MLflow)
- Python/Scala
- SQL
- ETL concepts
- Distributed data processing
- Data warehousing
- Cloud Platforms & Storage
What You'll Do
- Lead the design, development, and deployment of scalable data pipelines and ETL processes using Databricks (Spark, Delta Lake, MLflow);
- Architect and implement data lakehouse solutions, ensuring data quality, governance, and security;
- Optimize data workflows for performance and cost efficiency on Databricks and cloud platforms (Azure, AWS, or GCP);
- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights;
- Mentor and guide junior engineers, promoting best practices in data engineering and Databricks usage;
- Develop and maintain documentation, data models, and technical standards;
- Monitor, troubleshoot, and resolve issues in production data pipelines and environments;
- Stay current with emerging trends and technologies in data engineering and Databricks ecosystem;
Job Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field;
- 5+ years of experience in data engineering, with at least 2 years of hands-on experience with Databricks (including Spark, Delta Lake, and MLflow);
- Strong proficiency in Python and/or Scala for data processing;
- Deep understanding of distributed data processing, data warehousing, and ETL concepts;
- Experience with cloud data platforms (Azure Data Lake, AWS S3, or Google Cloud Storage);
- Solid knowledge of SQL and experience with large-scale relational and NoSQL databases;
- Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for data engineering;
- Experience with data governance, security, and compliance in cloud environments;
- Excellent problem-solving, communication, and leadership skills;
- English: Upper Intermediate level or higher;
What Do We Offer
The global benefits package includes:
- Technical and non-technical training for professional and personal growth;
- Internal conferences and meetups to learn from industry experts;
- Support and mentorship from an experienced employee to help you professional grow and development;
- Health insurance;
- Sports activities to promote a healthy lifestyle;
- Flexible work options, including remote and hybrid opportunities;
- Referral program for bringing in new talent;
- Work anniversary program and additional vacation days.
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