Assist in designing and implementing scalable and robust processes for ingesting and transforming complex datasets.
Designs, develops, constructs, maintains and supports data pipelines for ETL from a multitude of sources.
Creates blueprints for data management systems to centralize, protect, and maintain data sources.
Focused on data stewardship and curation, the data engineer enables the data scientist to run their models and analyses to achieve the desired business outcomes
Ingest large, complex data sets that meet functional and non-functional requirements.
Enable the business to solve the problem of working with large volumes of data in diverse formats, and in doing so, enable innovative solutions.
Design and build bulk and delta data lift patterns for optimal extraction, transformation, and loading of data.
Supports the organisation’s cloud strategy and aligns to the data architecture and governance including the implementation of these data governance practices.
Engineer data in the appropriate formats for downstream customers, risk and product analytics or enterprise applications.
Assist in identifying, designing and implementing robust process improvement activities to drive efficiency and automation for greater scalability. This includes looking at new solutions and new ways of working and being on the forefront of emerging technologies.
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Work with various stakeholders across the organization to understand data requirements and apply technical knowledge of data management to solve key business problems.
Provide support in the operational environment with all relevant support teams for data services.
Provide input into the management of demand across the various data streams and use cases.
Create and maintain functional requirements and system specifications in support of data architecture and detailed design specifications for current and future designs.
Support test and deployment of new services and features.
Provides technical leadership to junior data engineers in the team
MINIMUM QUALIFICATIONS/EXPERIENCE (REQUIRED FOR THE JOB)
Matric, with a degree in Computer Science, Business Informatics, Mathematics, Statistics, Physics or Engineering.
4+ years of data engineering experience
4+ years of experience with any data warehouse technical architectures, ETL/ELT, and reporting/analytics tools including , but not limited to , any of the following combinations (1) SSIS ,SSRS or something similar (2) ETL Frameworks, (3) Spark (4) AWS data builds
The candidate having DBA ability and knowledge across at least 2 platforms (example: TSQL, SAS, PSQL, IBM VSAM, DynamoDB and DB2) will also be beneficial.
Should be at least at a proficient level in at least one of Python or Java
Should be Proficient in bash SQL
Some experience with R, AWS, XML, json, cron will be beneficial
Experience with designing and implementing Cloud (AWS) solutions including use of APIs available.
Some experience with Dev/OPS architecture, implementation and operation would be advantageous.
Knowledge of Engineering and Operational Excellence using standard methodologies. Best practices in software engineering, data management, data storage, data computing and distributed systems to solve business problems with data.
Some experience in applying SAFe/Scrum/Kanban methodologies.
Knowledge and understanding of business process management lifecycle which covers the design, modelling, execution, monitoring, and optimization as well as business process re-engineering.
Good problem solving skills: The ability to exercise judgment in solving technical, operational, and organizational challenges, to identify issues proactively, to present solutions and options leading to resolution
Data Engineer
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