Data Engineer (Databricks)

Quick Facts

• Role: Data Engineer (Databricks)

Description

As a Data Engineer, you will design scalable data processing pipelines for streaming and batch workloads and build/transform data platforms using Databricks and related technologies. You will implement data governance and data management processes, contribute to CI/CD and MLOps, and collaborate with Data Science on ML use cases. Cloud delivery is central to the role (with a preference for Azure), along with support for data visualization via Power BI.

Responsibilities

• Design scalable data processing pipelines for streaming and batch processing

• Contribute to CI/CD and MLOps processes

• Develop applications to aggregate, process, and analyze data from diverse sources

• Collaborate with Data Science on machine learning projects (text/image analysis and predictive model building)

• Develop and organize data transformations using Databricks/dbt and Apache Airflow

• Translate business requirements into technical solutions and ensure optimal performance and quality

Requirements

• At least 3 years of commercial experience implementing/developing/maintaining Big Data systems

• Strong Python programming skills (clean code, OOP design)

• Experience designing and implementing data governance and data management processes

• Familiarity with Big Data technologies such as Databricks, Spark, Kafka, Airflow, Dagster, or dbt

• Experience implementing and deploying solutions in cloud environments (preferably Azure)

• Knowledge of building and deploying Power BI reports and dashboards

• Excellent understanding of dimensional data and data modeling techniques

• Excellent communication skills and consulting experience with direct client interaction

• Ability to work independently and take ownership of project deliverables

• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or related field

Benefits

• Supportive team focused on AI & Big Data

• International projects with global enterprises and cutting-edge startups

• Flexible work arrangements (remote or from modern offices/coworking spaces)

• Career paths, knowledge-sharing initiatives, language classes, and sponsored training/conferences (including Databricks and Anthropic training/certifications)

• Team-building events and integration budget

• Medical and sports packages, eye care, and well-being support (including psychotherapy and coaching)

• Full work equipment for optimal productivity

• Opportunities to boost your personal brand by speaking at conferences, writing, or participating in meetups

• Dedicated-buddy onboarding and an autonomous, friendly culture