Data Engineer (Databricks)

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.