Senior Data Engineer

Key responsibilities:

1. Creates data models in a structured data format to enable analysis thereof.
2. Designs and develops scalable extract, transformation and loading (ETL) packages from the business source systems and the development of ETL routines to populate data from sources,
3. Participates in the transformation of object and data models into appropriate database schemas within design constraints.
4. Interprets installation standards to meet project needs and produce database components as required.
5. Creates test scenarios and be responsible for participating in thorough testing and validation to support the accuracy of data transformations.
6. Accountable for running data migrations across different databases and applications, for example MS Dynamics, Oracle, SAP and other ERP systems.
7. Works across multiple IT and business teams to define and implement data table structures and data models based on requirements.
8. Accountable for analysis, and development of ETL and migration documentation.
9. Collaborates with various stakeholders to evaluate potential data requirements.
10. Accountable for the definition and management of scoping, requirements, definition, and prioritization activities for small-scale changes and assist with more complex change initiatives.
11. Collaborates with various stakeholders, contributing to the recommendation of improvements in automated and non-automated components of the data tables, data queries and data models.

To thrive in this role, you need to have:

1. Seasoned knowledge of the definition and management of scoping requirements, definition and prioritization activities.
2. Seasoned understanding of database concepts, object and data modelling techniques and design principles and conceptual knowledge of building and maintaining physical and logical data models.
3. Seasoned expertise in Microsoft Azure Data Factory, SQL Analysis Server, SAP Data Services, SAP BTP.
4. Seasoned understanding of data architecture landscape between physical and logical data models
5. Analytical mindset with excellent business acumen skills.
6. Problem-solving aptitude with the ability to communicate effectively, both written and verbal.
7. Ability to build effective relationships at all levels within the organization.
8. Seasoned expert in programing languages (Perl, bash, Shell Scripting, Python, etc.).

Academic qualifications and certifications:

1. Bachelor's degree or equivalent in computer science, software engineering, information technology, or a related field.
2. Relevant certifications preferred such as SAP, Microsoft Azure etc.
3. Certified Data Engineer, Certified Professional certification preferred.

Required experience:

1. Seasoned experience as a data engineering, data mining within a fast-paced environment.
2. Proficient in building modern data analytics solutions that delivers insights from large and complex data sets with multi-terabyte scale.
3. Seasoned experience with architecture and design of secure, highly available and scalable systems.
4. Seasoned proficiency in automation, scripting and proven examples of successful implementation.
5. Seasoned proficiency using scripting language (Perl, bash, Shell Scripting, Python, etc.).
6. Seasoned experience with big data tools like Hadoop, Cassandra, Storm etc.
7. Seasoned experience in any applicable language, preferably .NET.
8. Seasoned proficiency in working with SAP, SQL, MySQL databases and Microsoft SQL.
9. Seasoned experience working with data sets and ordering data through MS Excel functions, e.g. macros, pivots.

Workplace type:

Hybrid Working