Senior Data Software Engineer
Hybrid Krakow Full-time Senior Software Engineering
At a glance
Senior Software Engineering role at ActiveCampaign. Krakow · full-time · PLN 224,000–PLN 336,000 base.
SalaryStated by ActiveCampaign
PLN 224,000 – PLN 336,000
Base salary for this role, in PLN per year, as published in the posting.
RoleSoftware Engineering
SenioritySenior
LocationKrakow
WorkplaceHybrid
EmploymentFull-time
Base payPLN 224,000–PLN 336,000
PostedJun 15, 2026 · 4mo ago
Role brief
techroles summary, based on the employer's posting.
What you'll do
- Build and maintain high-throughput pipelines that move and transform data across systems
- Shape database schemas and use DDL and DML to improve performance and support future scale
- Set up automated tests, CI/CD and Terraform-based infrastructure so data systems stay 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 business terms
What you bring
- At least five years building and maintaining production data systems as a software engineer
- You can design data architectures and schemas that balance query speed with future growth
- You have managed and deployed infrastructure with Terraform, and bring strong automated testing and CI/CD practices
- You write advanced SQL, especially MySQL queries that need performance tuning
Who this fits
This senior role suits an engineer focused on production data systems, architecture and performance, with the communication skills to explain technical choices to both technical and non-technical colleagues. The position is based in Krakow and is hybrid.
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:
- 5+ 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