We are looking for 4 Data Engineers (Medior / Senior) to join a dynamic data team working on large-scale transformation and migration initiatives. You will be responsible for building and maintaining scalable, high-performance data pipelines, both in on-prem and AWS cloud environments. You will work with modern data frameworks and tools to enable clean, automated, and efficient data flows supporting business-critical analytics and reporting.
Language: English (required)
What are your responsibilities?
* Translate functional specifications into efficient technical designs
* Develop and maintain batch and real-time data pipelines using Python and PySpark
* Automate data workflows and orchestration using Apache Airflow
* Migrate legacy pipelines from on-prem to AWS cloud environments
* Perform data modeling, transformation, and reconciliation tasks
* Ensure high standards in code quality, testing, and deployment
* Monitor pipeline performance and improve processing efficiency
* Collaborate within Agile teams and contribute to solution architecture
* Support data-driven decision-making across departments
Who are we looking for?
* 2–5 years of experience for medior roles, 5+ years for senior roles in data engineering or software development
* Proficient in Python, PySpark, and SQL
* Strong experience with Apache Spark and Apache Airflow
* Solid knowledge of data modeling and data architecture principles
* Experience working in cloud environments, especially AWS (S3, Glue, Lambda, CI/CD tools)
* Familiar with both on-prem and cloud-based data ecosystems
* Agile mindset with experience working in Scrum/SAFe teams
* Strong analytical thinking, autonomy, and problem-solving skills
* Clear communicator and team player with a proactive attitude
* Bonus: experience with Scala, JavaScript, Informatica, or NoSQL technologies (MongoDB, Cassandra, etc.)
PS: We also work with freelancers