Data Engineer

We are seeking a skilled Data Engineer to design, build, and maintain robust data

pipelines and systems that ensure complete traceability of data from our

manufacturing tools and processes. This role is critical for enabling data-driven

decision-making and ensuring compliance with security and quality standards in a

fabless semiconductor environment.

Key Responsibilities

• Data Pipeline Development: Design, implement, and maintain scalable ETL

processes to collect, transform, and store data from multiple sources

(manufacturing tools, test systems).

• Data architecture: Design and implement data models and storage solutions

(e.g. relational databases, NoSQL systems, cloud-based warehouses) and

optimise data structures for query performance and cost efficiency.

• Data Integration: Consolidate heterogeneous data sources into a unified data

platform for traceability and analytics.

• Cloud & Infrastructure: Deploy and manage data solutions in cloud

environments (AWS, Azure, or GCP), ensuring high availability and

performance. Manage and deploy data infrastructure using tools like Airflow,

Spark, Kafka, etc.

• Data Modeling: Develop and optimize data models for traceability, reporting,

and advanced analytics.

• Monitoring & Quality: Implement data quality checks, monitoring, and alerting

to ensure data integrity and reliability.

• Security & Compliance: Apply best practices for data governance, encryption,

and access control to meet information security requirements (ISO 27001,

GDPR, etc.).

• Collaboration: Work closely with product engineers, production engineers and

business stakeholders to deliver data solutions aligned with business needs.

• Education: Bachelor's or Master's degree in Computer Science, Data

Engineering, or related field.

• Technical Expertise:

o Strong proficiency in SQL and experience with relational and NoSQL

databases.

o Hands-on experience with ETL tools (e.g., Apache Airflow, Talend, dbt).

o Proficiency in Python or Scala for data processing.

o Experience with big data frameworks (e.g., Spark, Hadoop) is a plus.

• Cloud Platforms: AWS (Glue, Redshift, S3), Azure (Data Factory, Synapse), or

GCP (BigQuery, Dataflow).

• Data Security: Knowledge of encryption, IAM, and compliance frameworks.

• Version Control & CI/CD: Git, Jenkins, Docker, Kubernetes or similar tools.

• Soft Skills: Strong problem-solving, communication, and documentation skills.

Preferred Experience

• Experience in manufacturing environments.
• Familiarity with traceability systems and industry standards.
• Knowledge of data lineage and metadata management tools.

Certifications (Nice to Have)

• AWS Certified Data Analytics or equivalent.
• Certified Information Systems Security Professional (CISSP) or similar.

Semi Zabala is a power semiconductor company dedicated to the design, manufacture