Senior Data Engineer @ INNOBO

Client : banking industry

Hourly Rate : up to 160 PLN + VAT

Location : Gdansk or Gdynia or Warsaw or Lodz, Poland

Work arrangement : hybrid, 2 days at the office, full-time

Key Competencies :

• Proficiency in programming languages like Python & Spark - minimum 5 years
• Understanding of algorithms and data structures, knowledge of statistics and linear algebra
• Experience with machine learning frameworks ( TensorFlow or PyTorch ), including training new ML models, refining existing ones, and deploying these models into user-friendly applications
• Solid understanding of distributed systems with experience in Hadoop / Hive ecosystem and / or other Big Data Technologies
• Responsible for overseeing databases and cloud platforms like AWS, Azure, and Google Cloud, making sure that your infrastructure remains scalable and secure as your business grows
• Proficient in SQL (Spark / Hive SQL) , previous experience in creating data flows
• Experience with BitBucket and GIT , code versioning and branching strategy
• Familiar with Agile / Safe framework
• Cloud AWS Experience will be a big plus

Nice-to-have knowledge and experience :

Client : banking industry

Hourly Rate : up to 160 PLN + VAT

Location : Gdansk or Gdynia or Warsaw or Lodz, Poland

Work arrangement : hybrid, 2 days at the office, full-time

,[Managed the lifecycle of machine learning models from development to deployment and monitoring, ensuring optimal performance and reliability, Implemented MLOps principles, including continuous integration, continuous delivery, testing, and monitoring, to streamline machine learning operations, Working with Spark & Python to define and maintain data ingestions and transformation, handling both real-time and batch data processing, Building distributed and highly parallelized big data processing pipeline which process massive amount of data (both structured and unstructured data) in near real-time, Leverage Spark to enrich and transform corporate data to enable searching, data visualization, and advanced analytics, Collaborated with cross-functional teams, including data scientists, DevOps engineers, and IT, to deliver high-quality machine learning solutions, Working closely with analysts and business stakeholders to develop analytics models, Help in optimizing our current MLOps practices and libraries, make applicable for wider range of use cases outside propensity models, Cloud solution exploration for AI / ML areas.] Requirements : Python, SQL, Spark, Data structures, Machine Learning, TensorFlow, PyTorch, Hadoop, Hive, Big Data, AWS, Bitbucket, Git, ML models Tools : . Additionally : International projects.