Streaming Data Engineer
Responsibilities
Data System Design: Design and implement robust, scalable data processing systems: this involves selecting appropriate storage technologies, designing schemas, and planning integration strategies.
Data Integration and ETL Development: Develop and maintain pipelines for data transformation, integration, and ETL processes. Ensure data quality and accessibility
Streaming Data Processing: Design, implement, test and maintain highly scalable real time stateless and stateful data transformations ensuring low latency and data quality
Performance Optimization: Monitor, tune, and optimize data applications and database performance. Address any issues that may affect data processing speeds or analytics capabilities
Consulting and Strategy: Provide expert advice and consultancy services to clients on data strategies, architecture choices, and technological advancements
Analytics and Business Intelligence Support: Assist in developing analytics platforms and business intelligence solutions, ensuring that data can be effectively transformed into actionable insights
Client Interaction: Work closely with clients to understand their business needs and technical requirements. Translate these requirements into effective data engineering solutions.
Benefits
Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more.
Language Courses – you'll have access to a multi-language learning platform enabling you to practice you language skills and learn new ones!
Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development.
Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions.
Qualifications
Educational Background: Bachelor’s or master’s degree in CS, Engineering, IT, or a related field.
Programming Language: Strong programming skills in languages such as Python, Java or Kotlin.
Cloud: Experience with public cloud providers AWS/Azure.
Database Technologies: Knowledge of SQL and NoSQL databases.
Expertise in Big Data Technologies: Familiarity with big data frameworks and tools like Spark, formats such as Apache Iceberg.
Streaming Technologies: Knowledge of the Kafka ecosystem (Kafka clusters, connectors and clients, Kafka Streams) and other streaming platforms (e.g. Flink)
Containerization: Experience in Docker, familiarity with Kubernetes is nice to have.
Data Modeling and Warehousing: Familiarity with data modeling and warehousing techniques.
Strong Analytical Skills: Ability to analyze complex data structures and derive insights to provide strategic guidance.
Excellent Communication: Strong interpersonal and communication skills to effectively collaborate with team members and clients.
Very good knowledge of English and Polish.
Problem Solving: Strong problem-solving skills and the ability to propose creative, efficient solutions to complex problems.
Nice to have experience with Databricks, DBT.
Availability to work in a hybrid mode with at least 2 visits to the office per month.
About Data Reply
Data Reply, as part of the Reply Group, offers a wide range of services to help customers to become data driven. The team is active in various industries and business areas and works closely with clients to enable them to achieve meaningful results through the effective use of data. Data Reply offers many years of experience in transformation projects on the topic of "Data Driven Enterprise". Our experts focus on the development of Streaming and Event-Driven applications, Data Platforms and Machine Learning solutions - automated, efficient and scalable - without compromising IT security.

Reply Polska Sp. z o. o.
Founded in Turin in 1996, we have grown into one of the most renowned IT & Consulting networks, with more than 16,000 experts in over 100 companies worldwide. Through small, international teams, we drive digital change.
Streaming Data Engineer
Streaming Data Engineer