Senior Data Engineer (AWS, Snowflake, Python)

Our client is a global technology and digital transformation organization specializing in software engineering and IT consulting, serving international clients across multiple industries. The company operates in a fast-paced, collaborative environment, with a strong focus on innovation, engineering excellence, and continuous professional development.

Role overview

We are seeking a Senior Data Engineer to join our team and drive the performance, reliability and scalability of our data platform. This role focuses on Snowflake optimization, pipeline automation and mentoring junior engineers while contributing to key architectural decisions.

Mandatory skills

• 5+ years of experience in data engineering

• Proficiency in SQL and Python for advanced query writing, optimization and automation

• Expertise in Snowflake, Databricks or Oracle

• Familiarity with AWS or Azure cloud services for data engineering

• Understanding of CI/CD pipelines using GitLab or similar tools

• Skills in Apache Airflow and dbt for workflow orchestration and data transformation

• English proficiency at B2 level or higher

Nice-to-have

• Knowledge of Terraform for infrastructure as code

• Familiarity with Kafka for event streaming and messaging

• Monitor Snowflake health and performance

• Debug and resolve failures in data ingestion or transformation

• Support platform tenants with Snowflake and Apache Airflow-related queries

• Build and maintain an end-to-end testing framework to ensure platform changes don't impact tenant flows across ingestion, transformation and orchestration

• Tune queries and optimize data storage for speed and cost efficiency

• Automate manual steps using GitLab CI/CD pipelines

• Support the release process

• Document data architecture, pipeline processes and best practices

• Collaborate with the Snowflake team to research and adopt new tools or frameworks

• Mentor junior colleagues and support their skill development

• Contribute to architectural decisions around data engineering implementation and tooling