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# Data Software Engineer

- **Company:** ActiveCampaign, LLC
- **Location:** Krakow, WI, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon S3, Data Analysis, Apache HTTP Server, Automation of Tests, Continuous Integration, Data Architecture, Data Manipulation Languages, Data Structures, Data Systems, Data Warehousing, Python (Programming Language), PostgreSQL, Machine Learning, MySQL, Standard Sql, Software Construction, Software Engineering, Feature Store, Data Processing, Data Storage Technologies, Sql Optimization, Snowflake, Apache Spark, Amazon Relational Database Service, Containerization, Kubernetes, Druid, Data Programming, Machine Learning Operations, Terraform, Looker Analytics, Data Pipelines, Docker
- **Published:** November 8, 2026
- **Apply:** https://www.juju.com/job/28_25197_29e98570521ceb79a8ee95e3ae17faf3

## About the Role

* Engineering Experience: 4+ years professional software engineering experience, with a proven track record of building and maintaining production-grade data systems
 * Data Architecture Experience: Deep understanding of modern data stack components. You should be comfortable designing and building schemas that balance performance with scalability
 * Infrastructure: Proficient with managing your own infrastructure in code, using tools like Terraform
 * Software rigor: Strong background in software engineering best practices, including automated testing and CI/CD
 * Advanced SQL and Optimization: Expert-level SQL skills (especially MySQL); you don't just write queries, you optimize for performance and scalability
 * Communication: You are able to have technical discussions internally as well as translate these ideas into non-technical conversations with stakeholders

184,000 zł - 276,000 zł a year

## Description

* Architecting and Building Pipelines: Design, develop, and maintain high-throughput data pipelines to move and transform data across our ecosystem
 * Data Modeling and Schema Design: Execute DDL and DML operations to manage and optimize our data structures
 * Engineering Excellence: Implement rigorous software engineering best practices, including automated testing, CI/CD pipelines, managing infrastructure as code, and monitoring of system health
 * Collaboration: Partner with Data Science and AI teams to engineer feature stores and automated MLOps Pipelines, enabling AI models to move from research to production

Technical environment:

 * Databases: MySQL, Amazon Aurora, Amazon RDS, PostgreSQL
 * Data 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