Senior Data Engineer

💼 Senior Data Engineer – AWS / Databricks / Python

📍 Remote | 🕓 Long-term cooperation

We are currently looking for an experienced Senior Data Engineer to join an international team and work on cutting-edge data projects. In this role, you’ll design and build scalable data pipelines, shape data transformation frameworks, and collaborate closely with analysts and data scientists to deliver impactful business solutions.

Key Responsibilities

• Design, develop, and maintain robust data pipelines to extract and process data from multiple sources into data lakes and data warehouses.

• Define and implement data transformation rules and data models.

• Collaborate with Product Analysts, Data Scientists, and Machine Learning Engineers to ensure data is clean, structured, and business-ready.

• Implement data quality checks, maintain data catalogues, and leverage orchestration, logging, and monitoring tools.

• Apply best practices in information architecture, version control (Git), and branching strategies.

• Build ELT/ETL pipelines using test-driven development methodologies.

Required Skills & Experience

• 5–8 years of hands-on experience in data engineering or similar roles.

• Strong knowledge of AWS services such as S3, IAM, Redshift, SageMaker, Glue, Lambda, Step Functions, and CloudWatch.

• Practical experience with Databricks or similar platforms (e.g., Dataiku).

• Proficiency in Python or Java, SQL (preferably Redshift), Jenkins, CloudFormation, Terraform, Git, and Docker.

• 2–3 years of experience with Spark/PySpark.

• Familiarity with data quality frameworks, orchestration tools, and SDLC documentation.

• Excellent communication skills and the ability to work collaboratively in cross-functional teams.

• Knowledge of DSCS and DPTM is a strong plus.