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.)
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