Streaming Data Engineer

O projekcie Develop yourself and the digital future - at Reply!

Reply specialises in designing and implementing solutions based on new communication channels and digital media. Structured as a network of highly specialised companies, Reply supports leading European industrial groups in sectors such as Telco & Media, Industry and Services, Banking and Insurance, and Public Administration, helping define and develop business models enabled by new paradigms such as AI, Cloud Computing, Digital Media, and the Internet of Things. Reply’s services include Consulting, System Integration, and Digital Services.

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.

Zakres obowiązków

• Streaming Data Processing: Design, implement, test and maintain highly scalable real-time stateless and stateful data transformations, ensuring low latency and data quality
• 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
• 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

Wymagania

• Educational Background: Bachelor’s or master’s degree in CS, Engineering, IT, or a related field
• Streaming Technologies: Knowledge of the Kafka ecosystem (Kafka clusters, connectors and clients, Kafka Streams) and other streaming platforms (e.g. Flink)
• 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
• 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

Oferujemy

• Sport subscription
• Training budget
• Private healthcare
• Flat structure
• Lunch card
• Small teams
• International projects
• Free coffee
• Bike parking
• Free beverages
• Mobile phone
• In-house trainings
• Modern office
• Startup atmosphere
• No dress code