About the Role
We are seeking a highly skilled Data Engineer to join our high-impact team building robust, cloud-native data infrastructure that supports machine learning and analytics workflows at scale.
Key Responsibilities
* Design and implement scalable ETL/ELT pipelines on Databricks using Spark, Delta Lake, and Python.
* Develop orchestration logic using tools such as AWS Step Functions, Lambda, or Databricks Workflows.
* Contribute to medallion architecture layers (Bronze, Silver, Gold) for structured data processing.
* Collaborate on infrastructure provisioning and pipeline automation using Terraform and GitHub Actions.
* Troubleshoot Spark job performance and help ensure reliable, efficient data pipelines.
We work closely with platform engineers, DevOps, and data scientists, collaborating on ingestion, transformation, orchestration, and data reliability for production-grade pipelines.
Requirements
* 3–6 years of experience in data engineering or data platform roles.
* Solid experience with Databricks and Delta Lake, including job and cluster setup.
* Strong skills in PySpark, SQL, and scripting for data transformation.
* Familiarity with AWS services: S3, Lambda, Step Functions, IAM, CloudWatch.
Benefits
* Flexible working hours.
* Coworking space financial coverage.
* English language lessons on all levels.
* Performance financial incentives.
* Paid courses and certifications.
* Participation at international conferences.
About Us
We partner with industry leaders like AWS, Google, and Databricks to deliver solutions across all layers of the modern technology stack. Our distributed team collaborates on innovative commercial and open-source projects. We commit to innovation and excellence, making us a trusted partner for leading technology companies and startups.
We value continuous learning and teamwork. If you're passionate about leveraging AI and cutting-edge methodologies to drive efficiency and precision, we'd love to hear from you.