Tillbaka till jobbBrådskandesam@veritaz.se
Data Automation Engineer - 19834
ITSenior
Gothenburg, SwedenFull-time · On-site Publicerad 1 oktober 2026 Ansök senast 8 oktober 2026
Språk: EnglishMinsta erfarenhet: 5 år
Sam Agassi
HR Administrator
Efterfrågade kompetenser
SnowflakeSQL & dbtPython Automation & Streamlit
Om tjänsten
Assignment Description
We are looking for a Senior Data and Marketing Automation Engineer to join a Customer Communication Platform initiative.
The role focuses on building, developing and maintaining data and marketing automation capabilities using Snowflake, dbt, SQL, Iterable, Python and Streamlit.
What You Will Work On
- Develop and maintain data solutions using Snowflake
- Build and manage data transformation pipelines using dbt
- Develop and optimize SQL queries and data models
- Work with Iterable for customer communication and marketing automation
- Develop automation solutions using Python
- Build internal tools and applications using Streamlit
- Support customer communication and marketing automation workflows
- Ensure data quality, reliability and scalability
- Develop and improve data pipelines
- Collaborate with data, marketing and technology teams
- Contribute to the development of the Customer Communication Platform
What You Bring
- Strong experience with Snowflake
- Strong SQL skills
- Hands-on experience with dbt
- Strong Python development and automation experience
- Experience with Iterable
- Experience with Streamlit
- Strong data engineering and data modelling knowledge
- Experience building data pipelines and automation solutions
- Understanding of customer communication and marketing automation
- Strong analytical and problem-solving skills
- Good communication and collaboration skills
Meritorious
- Experience with customer communication platforms
- Experience with marketing technology
- Experience with data science or machine learning
- Experience with cloud data platforms
- Experience with event-driven data pipelines
- Experience with Power BI or other BI tools
- Experience with data quality and governance
- Experience with large-scale customer data environments