Machine Learning Data Engineer

Join us, and enhance data solutions with the latest technologies and tools!

Krakow-based opportunity with the possibility to work 80% remote.

As a Machine Learning Data Engineer, you will be working for our client, a leading global financial institution, known for building innovative digital solutions and transforming the banking industry. You will play a key role in supporting their data and digital transformation initiatives by developing and optimizing data engineering processes. Working with cutting-edge technologies, you’ll contribute to the development of robust and scalable data solutions for critical financial services, handling everything from data pipelines to cloud integrations. You’ll be part of a dynamic team working on both greenfield projects and established banking applications.

Your main responsibilities:

• Developing and optimizing data engineering processes
• Building robust, fault-tolerant data solutions for both cloud and on-premise environments
• Automating data pipelines to ensure seamless data flow from ingestion to serving
• Creating well-tested, clean code in line with modern software engineering principles
• Working with cloud technologies (AWS, Azure, GCP) to support large-scale data operations
• Supporting data transformation and migration efforts from on-premise to cloud ecosystems
• Designing and implementing scalable data models and schemas
• Maintaining and enhancing big data technologies such as Hadoop, HDFS, Spark, and Cloudera
• Collaborating with cross-functional teams to solve complex technical problems
• Contributing to the development of CI/CD pipelines and version control practices

You’re ideal for this role if you have:

• Strong experience in the Data Engineering Lifecycle, especially in building data pipelines
• Proficiency in Python, Pyspark, and the Python ecosystem
• Experience with cloud platforms such as AWS, Azure, or GCP (preferably GCP)
• Expertise in Hadoop on-premise distributions, particularly Cloudera
• Experience with big data tools such as Spark, HDFS, HIVE, and Databricks
• Knowledge of data lake formation, data warehousing, and schema design
• Strong understanding of SQL and NoSQL databases
• Ability to work with data formats like Parquet, ORC, and Avro
• Familiarity with CI/CD pipelines and version control tools like Git
• Strong communication skills to collaborate with diverse teams

It is a strong plus if you have:

• Experience with ML models and MLOps
• Exposure to building real-time event streaming pipelines with tools like Kafka or Apache Flink
• Familiarity with containerization and DevOps practices
• Experience in data modeling and handling semi-structured data
• Knowledge of modern ETL and ELT processes
• Understanding of the trade-offs between different data storage technologies

#GETREADY  to meet with us!

We would like to meet you. If you are interested please apply and attach your CV in English or Polish, including a statement that you agree to our processing and storing of your personal data. You can always also apply by sending us an email at recruitment@itds.pl.

Internal number #6506