Job Brief
Design, develop, and maintain internal data services, automation flows, CI/CD infrastructure, and database-related tooling.
Job Description
- Design, develop and maintain data pipelines, ETL/ELT flows, and integrations between internal engineering systems
- Design and own the DevOps framework for the company and enable the automation infrastructure used by engineering teams
- Build automation tools to improve data processing, tooling, and development workflows
- Develop and help optimizing the in-house database-related services, including SQL queries, indexing, stored procedures, performance tuning, and monitoring
- Ensure data security, permissions, access control, and data integrity across internal systems
- Collaborate with cross-functional teams to understand requirements, solve technical issues, and improve internal developer and customer-facing platforms
Required Skills and Experience
- Bachelor’s degree or higher in Computer Science, Software Engineering, EE, Information Systems, or a related field
- Minimum 8+ years of experience as a Dataflow and DevOps development, Backend Engineer, Data Engineer, or similar role
- Strong experience with Python
- Strong SQL skills, including query optimization, indexing, stored procedures, and performance tuning
- Experience with ETL/ELT processes, data pipelines, and integration between systems
- Strong experience with automation scripting language (ex: Groovy), data processing, and tooling
- Experience with Docker, Kubernetes, Jenkins and CI/CD frameworks
- Familiar with developing in Linux and Windows environments
- Experience with backup, restore, migration, monitoring, and database maintenance processes
- Understanding of data security, permissions, access control, and data integrity practices
- Experience with Git, Jira, and Agile development workflows
- High English skills: listening, speaking, and reading (C1-2)
Nice to have
- Past experience with CloudBees, Antifactory, and integrating them into a secure system
- Strong experience with relational databases such as PostgreSQL and Pgvector, MySQL, and NoSQL
- Experience with cloud database services such as AWS RDS, Azure SQL, Google Cloud SQL, or similar
- Experience with database schema design, data modelling, and database normalization
- Experience with AI agents and AI automation
- Familiarity with database replication, clustering, high availability, and disaster recovery
- Experience with BI/reporting tools or data visualization platforms
- Experience with backup solutions and backup strategies
- Experience working in an R&D, semiconductor, embedded systems, or hardware/software engineering environment
- Experience and background in MAL, datasets, and MAL Python libraries.
- Experience in JAVA
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