Data Software Engineer
Hybrid Krakow Full-time Mid-level Software Engineering
At a glance
Mid-level Software Engineering role at ActiveCampaign. Krakow · full-time · PLN 184,000–PLN 276,000 base.
SalaryStated by ActiveCampaign
PLN 184,000 – PLN 276,000
Base salary for this role, in PLN per year, as published in the posting.
RoleSoftware Engineering
SeniorityMid-level
LocationKrakow
WorkplaceHybrid
EmploymentFull-time
Base payPLN 184,000–PLN 276,000
PostedMay 1, 2026 · 5mo ago
Role brief
techroles summary, based on the employer's posting.
What you'll do
- Design and maintain high-throughput pipelines that transform data across systems
- Shape database schemas and use DDL and DML to improve performance and support future growth
- Build automated tests, CI/CD workflows and Terraform infrastructure to keep data systems reliable
- Work with data science and AI teams on feature stores and MLOps pipelines that bring research into production
- Monitor Kubernetes, Docker and Airflow environments, and explain data architecture to stakeholders in clear terms
What you bring
- At least four years in software engineering, including building and supporting production data systems
- You can design data architectures and schemas that balance current query speed with long-term scalability
- You have used Terraform to provision and manage infrastructure, and bring strong automated testing and CI/CD practices
- You have advanced SQL skills, especially in MySQL, and can tune complex queries for performance
Who this fits
This mid-level role suits a software engineer with production data systems experience who can work across engineering and stakeholder conversations. It is based in Krakow, Poland, with a hybrid arrangement.
From the employer
What your day could consist of:
- Architect and Build Pipelines by designing, developing, and maintaining high-throughput data pipelines that seamlessly transform data across our ecosystem
- Execute Data Modeling and Schema Design, utilizing DDL and DML operations to optimize data structures for both performance and long-term scalability
- Champion Engineering Excellence by implementing automated testing, CI/CD pipelines, and Infrastructure as Code (Terraform) to ensure system health and reliability.
- Collaborate Cross-Functionally with Data Science and AI teams to engineer feature stores and automated MLOps pipelines, moving cutting-edge research into live production environments
- Drive System Monitoring and health checks, ensuring our containerized and orchestrated environments (Kubernetes, Docker, Airflow) run at peak efficiency.
- Act as a Technical Advisor to stakeholders, translating complex data architectures into clear, non-technical conversations that guide business decisions
Technical environment:
- Databases: MySQL, Amazon Aurora, Amazon RDS, PostgreSQL
- ata Storage and Analytics: AWS S3, Apache Iceberg, Snowflake, Apache Druid, Looker
- Data Processing and Transformation: Apache Spark, DBT
- Languages: Python (primary)
- Infrastructure as Code: Terraform
- Containerization and Orchestration: Kubernetes, Docker, Airflow
The Ideal Candidate Will Bring:
- 4+ years of professional software engineering experience, with a proven track record of building and maintaining production-grade data systems.
- Deep Data Architecture expertise, with the ability to design modern data stack components and schemas that balance immediate performance with future growth.
- Proficiency in Infrastructure as Code, specifically using Terraform to manage and deploy your own infrastructure.
- A high level of software rigor, including a strong background in automated testing, CI/CD, and general software engineering best practices
- Expert-level SQL skills (particularly MySQL), with a focus on optimizing complex queries for maximum performance.
- Experience in a modern technical environment, ideally having worked with Python, AWS (S3, Aurora, RDS), Snowflake, Apache Spark, and DBT
- Exceptional communication skills, with the talent to distill complex technical concepts into clear, actionable insights for both technical and non-technical peers