Data Engineer

Description KEY PERFORMANCE INDICATORS

• Design and implement a scalable and efficient data engineering platform

• The integration of data from multiple sources: organized, disorganized, structured and/or unstructured, into a centralized data repository. Creating and evolving data models, schemas and repositories to efficiently store and process data, accomplishing this through well designed, implemented and maintained ETL pipelines.

• Be responsible for the detailed cataloguing of all data assets within Columbus (from his/her area of responsibility), not only for own use, but also to assist data professionals as they analyze available data.

• Data quality and governance will be ensured and enforced by designing and implementing data quality standards, as well as governance policies, holding him/her accountable for architectures and/or data systems that promote data reliability, scalability and quality.

• Will ensure data security and compliance to privacy regulations by developing and implementing the required security protocols and access controls. Throughout all this he/she will continually optimize the data repository’s query and processing performance, ensuring quick and efficiently processed data.

• Internally the engineer has direct interfaces and interaction with the Production and Distribution departments (client oriented), the Engineering department (Control and measuring interfaces, both client and provider oriented), Technical department (process optimization, client oriented), OPS Planning (scheduling aspects, client oriented), and other IT Teams (L2, L3 and L4 teams, main providers).

• Externally the engineer would liaise with external system suppliers, process/data technology consultants, and application software suppliers. Cooperation with external stakeholders like customers and/or suppliers are also frequent, in order to integrate external data systems with Columbus Stainless systems

QUALIFICATION A Bachelor's or Master’s degree in Computer Science, Data Science, or related domain of study EXPERIENCE

Minumum of 2 years, to 6 years experince (years of experince will determine the appointment Grade)

RELEVANT SKILLS/COMPETENCIES

• Minimum of 4 years Data modelling, Data integration (ETL), System architecture design and System optimization experience.

• Minimum of 3 years Software design and engineering principles experience.

• Minimum of 2 years Project management experience.

CLOSING DATE 06th April 2025

Requirements KEY PERFORMANCE INDICATORS

• Design and implement a scalable and efficient data engineering platform

• The integration of data from multiple sources: organized, disorganized, structured and/or unstructured, into a centralized data repository. Creating and evolving data models, schemas and repositories to efficiently store and process data, accomplishing this through well designed, implemented and maintained ETL pipelines.

• Be responsible for the detailed cataloguing of all data assets within Columbus (from his/her area of responsibility), not only for own use, but also to assist data professionals as they analyze available data.

• Data quality and governance will be ensured and enforced by designing and implementing data quality standards, as well as governance policies, holding him/her accountable for architectures and/or data systems that promote data reliability, scalability and quality.

• Will ensure data security and compliance to privacy regulations by developing and implementing the required security protocols and access controls. Throughout all this he/she will continually optimize the data repository’s query and processing performance, ensuring quick and efficiently processed data.

• Internally the engineer has direct interfaces and interaction with the Production and Distribution departments (client oriented), the Engineering department (Control and measuring interfaces, both client and provider oriented), Technical department (process optimization, client oriented), OPS Planning (scheduling aspects, client oriented), and other IT Teams (L2, L3 and L4 teams, main providers).

• Externally the engineer would liaise with external system suppliers, process/data technology consultants, and application software suppliers. Cooperation with external stakeholders like customers and/or suppliers are also frequent, in order to integrate external data systems with Columbus Stainless systems

QUALIFICATION A Bachelor's or Master’s degree in Computer Science, Data Science, or related domain of study EXPERIENCE

Minumum of 2 years, to 6 years experince (years of experince will determine the appointment Grade)

RELEVANT SKILLS/COMPETENCIES

• Minimum of 4 years Data modelling, Data integration (ET