Must have

• Apache Spark

• Apache Kafka

• Microservice architecture

• Data

• Databricks

• Batch

• Java

• SQL

• CI/CD

• Spark

• Polish (Fluent)

• English (Fluent)

Nice to have

• DDD

• Azure

• Docker

Requirements description

Personal Requirements:

•    Have 4+ years of Apache Spark experience and have faced various data engineering challenges in batch or streaming

•    Have an interest in stream processing with Apache Spark Structured Streaming on top of Apache Kafka

•    Have experience leading technical solution designs

•    Have experience with distributed systems on a cloud platform

•    Have experience with large-scale systems in a microservice architecture

•    Are familiar with Git and CI/CD practice s and can design or implement the deployment process for your data pipelines

•    Possess a proactive approach and can-do attitude

•    Are excellent in English and Polish, both written and spoken

•    Have a higher education in computer science or a related field

•    Are a team player with strong communication skills

Nice to have requirements:

•    Apache Spark Structured Streaming

•    Azure

•    Domain Driven Development

•    Docker containers and Kubernetes

•    Message brokers (i.e. Kafka) and event-driven architecture

•    Agile/Scrum

Offer description

Are you ready to join our international team as a Lead / Senior Data Engineer? We shall tell you why you should...

What product do we develop?

We are building an innovative solution, KMD Elements, on Microsoft Azure cloud dedicated to the energy distribution market (electrical energy, gas, water, utility, and similar types of business). Our customers include institutions and companies operating in the energy market as transmission service operators, market regulators, distribution service operators, energy trading, and retail companies.

KMD Elements delivers components allowing implementation of the full lifecycle of a customer on the energy market: meter data processing, connection to the network, physical network management, change of operator, full billing process support, payment, and debt management, customer communication, and finishing on customer account termination and network disconnection.

The key market advantage of KMD Elements is its ability to support highly flexible, complex billing models as well as scalability to support large volumes of data. Our solution enables energy companies to promote efficient energy generation and usage patterns, supporting sustainable and green energy generation and consumption.

We work with always up-to-date versions of:

• Apache Spark on Azure Databricks

• Apache Kafka

• Delta Lake

• Java

• MS SQL Server and NoSQL storages like Elastic Search, Redis, Azure Data Explorer

• Docker containers

• Azure DevOps and fully automated CI/CD pipelines with Databricks Asset Bundles, ArgoCD, GitOps, Helm charts

• Automated tests

How do we work?

#Agile #Scrum #Teamwork #CleanCode #CodeReview #Feedback #BestPracticies

• We follow Scrum principles in our work – we work in biweekly iterations and produce production-ready functionalities at the end of each iteration – every 3 iterations we plan the next product release

• We have end-to-end responsibility for the features we develop – from business requirements, through design and implementation up to running features on production

• More than 75% of our work is spent on new product features

• Our teams are cross-functional (7-8 persons) – they develop, test and maintain features they have built

• Teams’ own domains in the solution and the corresponding system components

• We value feedback and continuously seek improvements

• We value software best practices and craftsmanship

Product principles:

• Domain model created using domain-driven design principles

• Distributed event-driven architecture / microservices

• Large-scale system for large volumes of data (>100TB data), processed by Apache Spark streaming and batch jobs powered by Databricks platform

Our offer:

• Contract type: B2B

• Work Mode: Flexible — this role supports on-site, hybrid, and remote arrangements, depending on your individual preferences.

• Occasional on-site presence may be required— for example, onboard new team members, explore new business domains, or refine requirements in close collaboration with stakeholders or team building activities.

Your responsibilities

1. Develop and maintain the leading IT solution for the energy market using Apache Spark, Databricks, Delta Lake, and Apache Kafka
2. Have end-to-end responsibility for the full lifecycle of features you develop
3. Design technical solutions for business requirements from the product roadmap
4. Maintain alignment with architectural principles defined on the project and organizational level
5. Ensure optimal performance through continuous monitoring and code optimization.
6. Refactor existing code and enhance system architecture to improve maintainability and scalability.

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