Strona główna

• You are a software craftsman with solid foundation of System/Platform Engineering, Functional Programming (FP) and with managing the complexity of Distributed Systems.
• You have 5+ years of Data and/or Platform Engineering experience in building and managing highly-scalable distributed systems.
• You have at least Master Degree in Computer Science or related field of study, such as AI/Machine Learning.
• You have strong engineering and problem-solving skills with a passion for FP (with typed FP Language, e.g., Scala) and Java.
• You have excellent knowledge in working with Flink, Spark and Kafka in a production environments.
• You have hands on experience in operationalizing and managing Machine Learned Models and its continuous evaluation, and building complex data ingestion and transformation pipelines for batch and real-time data.
• You have experience with at lease on of the following database technologies in managing production systems: Cassandra, Elastic , Redis, PostgreSQL, MongoDB or similar.
• You are fluent in written and spoken English;
• You have the enthusiasm for helping others to be successful and a drive for taking it on and making it happen;
• You embrace challenges in a fast changing and complex environment;
• You are a naturally collaborative person who listens and invests in others to achieve common goals;
• You have a can-do attitude (self-steering).
• Most importantly: You believe that the change is the only constant. You have the right attitude to learn new programming paradigms and technologies, and to establish it in the organization

• Experience in the Financial Services is considered a plus, at least you have an affinity with it;
• Being a committer to Open Source repos is a strong plus;
• Knowledge of Machine learning (preferred experience with real implementations), or at least strong affinity with it;
• Good understanding of automated testing frameworks;
• Experience with working in an agile/scrum way, but at least you should have a strong willingness to do so;
• Knowledge of many of the following:
  • Programming Languages: Haskell, Python, R.
  • Scheduler: Airflow or similar.
  • Web services frameworks: Http4s, Akka Http, Finch or similar.
  • Container Technologies: Docker, Kubernetes or similar.
  • Distributed System: HDFS, Ceph, Cassandra.
  • Cloud: Azure, GCP.
  • Encryption and security (SSL, certificate handling).
  • CD for Machine Learning pipeline (CD4ML).

Your role

As a Data Engineer you will be joining ING’s Advanced Analytics global organization and will partner with Data Scientists and Machine Learning Engineers in our center of expertise to research, design and implement leading-edge algorithmic products. We are looking for a passionate, Senior-level, Data/Platform Engineer to help us in the domain of applied machine learning. By designing and testing practical use-cases for business, you help steer the team in creating value for our customers.

You will be part of the technology team, taking care of software and data engineering challenges associated with data science and machine learning. You will be involved in serving and deploying models and putting research into production. Through collaboration with architects, machine learning engineers and data scientists, you will take responsibility in making sure that data flows from the various source systems in ING to the Data Analytics production platform. You will be working on different types of data, both structured and unstructured. As a Data/Platform Engineer you will design data architecture for incoming projects. Your passion is to work with the latest and greatest technologies that make working with large amounts of data easy, you are pro-active in keeping yourself up to date and are always searching for new ways to discover new technologies.

You will be responsible for:

• Designing and implementing data architecture as part of the Data Platform Squad;
• Building complex data pipelines for analytics software development;
• Working closely with data scientists to operationalize their models into production and run it at a scale in a distributed manner in batch, request-response or streaming manner.
• Managing and further developing distributed systems and clusters for both batch as well as streaming data with Spark, Flink, Kafka etc.
• Building Developer Experience tooling to enable fast, reproducible, and organized experimentation by model developers.

Think Forward! Our purpose is to empower people to stay a step ahead in life and in business. We are an industry-recognized strong brand with positive recognition from customers in many countries, strong financial position, omnichannel distribution strategy, and international network. If you want to work at a place where we believe that you can live by the Agile manifesto without jeopardizing the necessary continuity, compliance and QA measures, where we are committed to deliver stable and secure services to end-users, and where we have a 'no-nonsense' getting-things done mentality, please read on!

At ING Tech Poland and ING globally we follow the Agile approach and mindset. We use flexible frameworks like Scrum and Kanban at our everyday work. We are innovative and we trust people we work with. The broad autonomy our employees have, stimulates motivation and creativity what allows us to adapt to the changing requirements of business partners. Small units called squads are the core of our organization. They have clear vision of products, overcome challenges autonomously and based on team cooperation, work out the most flexible and effective way of working.

ING Tech Poland we create new teams in data analytics area, alongside RiskHub providing modelling services for Risk Department.

The newly onboarded in Poland ING Analytics Data, Tools & Technology (DTT) team is responsible for driving overall strategy and roadmap for analytics platforms of ING globally, for realizing ING as one of the leaders in data-driven organizations, within the banking sector and beyond. We do this by combining Big Data technology with Data Science to deliver high-value solutions and AI/ML products for our organization. We collaborate with the Data Engineers, Data Scientists, and Machine Learning Engineers in our center of expertise to research, design, and implement leading-edge algorithmic products. We work in a fun and creative environment and we’re dedicated to bringing out the best in both each other and our projects.

Our Stack

Within DTT team as one of the leaders in data-driven organizations we mainly use the following technologies and frameworks:

• Scala
• Akka
• Java
• Python
• Javascript (Polymer)
• Kubernetes /Docker
• Ceph
• Spark
• Flink
• Kafka