Data Engineer

KadAgency Global AB; Lunds kommun; On-site; SEK 800,000 - 1,000,000; Full time

Benefits offered by this job

Energy transition focus

Hands-on data engineering

Collaborative engineering culture

Job summary

KadAgency Global AB in Lund, Sweden, is seeking a Data Engineer to develop and enhance the data infrastructure behind the RE:Flex platform. You will work with real-time IoT data, cloud resources and modern databases to ensure reliable collection, processing and delivery of data.

You will collaborate with backend, DevOps and ML teams, contribute to code quality, documentation and platform reliability, and help build scalable pipelines using Python, SQL and cloud services.

Qualifications

• 5+ years of professional data engineering or backend development experience.
• Strong Python programming and SQL skills.
• Experience with data pipelines, APIs and cloud services.
• Experience with Docker and Kubernetes.
• Proficient English communication.

Responsibilities

• Develop and maintain data ingestion and processing pipelines.
• Build real-time and batch data flows using MQTT and cloud services.
• Develop backend APIs and data services for the platform.
• Ensure data quality with validation, monitoring and backfill.
• Collaborate with DevOps, ML engineers and business teams.

Skills

Python

SQL

English

APIs

Data Engineering

Education

Bachelor's degree in Computer Science / Software Engineering / Data Engineering

Tools

Docker

Kubernetes

Google Cloud Platform

TimescaleDB

PostgreSQL

MongoDB

MQTT

Job description

We are looking for a Data Engineer to develop, maintain and improve the data infrastructure and backend services supporting our RE:Flex platform.

The role involves working with real-time IoT data, cloud infrastructure, databases and data pipelines to ensure reliable data collection, processing, storage and delivery.

You will work closely with backend developers, DevOps engineers, machine learning engineers and other teams across the business, operations and finance. Alongside hands‑on development, you will contribute to technical improvements, code reviews, troubleshooting, documentation and knowledge sharing.

Key Responsibilities

Data Engineering and Pipelines

• Develop and maintain Python-based services for collecting and processing data from connected energy devices, including battery systems and meters.
• Build and improve real-time and batch data pipelines using MQTT, Google Cloud Pub/Sub and other messaging technologies.
• Integrate data from external APIs, energy market platforms and other relevant data sources.
• Implement data validation, error handling, retry mechanisms and safe backfilling to improve data quality and reliability.
• Develop and maintain data processing workflows, including aggregation and transformation of time-series data.

Backend Development and Cloud Infrastructure

• Develop and maintain backend APIs and services for accessing real-time and historical platform data.
• Work with databases and storage solutions such as BigQuery, TimescaleDB, PostgreSQL and MongoDB, depending on application requirements.
• Develop, deploy and maintain containerised applications using Docker and Kubernetes.
• Contribute to cloud infrastructure improvements, primarily within Google Cloud Platform.
• Support integrations between data services, backend applications and other platform components.

Data Quality, Monitoring and Reliability

• Monitor data pipelines, database performance and service reliability using tools such as Grafana and cloud monitoring services.
• Investigate data inconsistencies, missing records, processing failures and other production issues.
• Improve data processing performance, scalability and operational stability.
• Implement appropriate data quality checks, logging, monitoring and alerting.
• Support incident investigation, troubleshooting and implementation of technical fixes.

Energy Market and Business Data

• Support data processing and integration for energy market operations, including market prices, schedules, measurements and settlement information.
• Develop and maintain data workflows used for operational reporting, revenue calculations and customer invoicing.
• Work with market operations, finance and other business teams to understand data requirements and resolve discrepancies.
• Help ensure data consistency and traceability across relevant systems and integrations.

Technical Collaboration and Documentation

• Participate in technical planning, architecture discussions and code reviews.
• Coordinate with backend, DevOps, machine learning and other engineering teams on data-related implementations.
• Support onboarding and knowledge sharing with other engineers.
• Maintain technical documentation, data flow descriptions and operational procedures.
• Contribute to continuous improvements in development practices, deployment processes and platform reliability.

Required Qualifications

• Relevant education in Computer Science, Software Engineering, Data Engineering or a related technical field, or equivalent practical experience.
• At least 5 years of professional experience in data engineering, backend development or a related software engineering role.
• Strong programming skills in Python and good knowledge of SQL.
• Experience developing data pipelines, backend services and REST APIs.
• Experience working with relational or NoSQL databases and cloud-based data processing.
• Familiarity with messaging systems, streaming data or asynchronous processing.
• Practical experience with Docker and cloud infrastructure.
• Understanding of software development practices, version control, testing and debugging.
• Good communication skills and the ability to collaborate with technical and non-technical teams.
• Professional working proficiency in English.

Meriting Experience

• Google Cloud Platform, particularly Pub/Sub, BigQuery and Cloud Storage.
• MQTT, IoT telemetry or real-time data processing.
• TimescaleDB, PostgreSQL, MongoDB or other time-series and NoSQL databases.
• Kubernetes, CI/CD pipelines and infrastructure automation.
• Dagster, Airflow or similar data orchestration tools.
• Monitoring and observability tools such as Grafana and Prometheus.
• Experience with data reconciliation, reporting or invoicing integrations.
• Knowledge of battery energy storage systems, energy flexibility services or Nordic electricity markets.
• Experience supporting technical onboarding, documentation or cross-team coordination.

What We Offer

• The opportunity to contribute to Sweden's energy transition through real-world energy technology solutions.
• Hands‑on experience working with real-time data, cloud infrastructure and distributed energy systems.
• A collaborative engineering environment with opportunities to contribute to technical decisions and platform improvements.
• The opportunity to work across data engineering, backend development and energy market applications.

Utbildning

Krav

• Eftergymnasial utbildning två år eller längre