Job Description

Minimum requirements

• Bachelors degree in Computer Science, Business Informatics, Mathematics, Statistics or Engineering
• 4 - 5 years relevant data engineering experience.
• A strong understanding of data structures, algorithms, and effective software design.
• Significant experience working with structured and unstructured data at scale and different data stores such as key-value, document, columnar, etc. as well as traditional RDBMS and data warehouses.
• Good programming, performance tuning and troubleshooting skills using programming languages such as python, scala, java and C# .
• Practical experience with Apache Spark and AWS services such as Redshift, Glue, Lambda, EMR, S3, IAM, RDS, etc.
• Experience wrangling terabytes of big, complicated, imperfect data.
• Experience with designing and implementing Cloud (AWS) solutions including use of APIs available.
• Experience with DevOPS architecture, implementation and operation would be advantageous.
• Experience with version control systems such as Git, SVN.
• Excellent verbal and written communication skills; must work well in an agile, collaborative team environment.
• 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 would be advantageous.
• 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

• Assist in designing and implementing scalable and robust processes for ingesting and transforming large data sets.
• Assist in the design and implementation of data pipelines from a variety of data sources and support the maintenance thereof.
• 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.
• Build bulk and delta data patterns for optimal extraction, transformation, and loading of data.
• Supports the organisations cloud strategy and alignment to data architecture and data governance.
• Engineer data in the appropriate formats for downstream consumption for analytics or Enterprise applications.
• Assist in the development of APIs to expose the data to Enterprise Applications and 3rd party vendors.
• 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.
• Work with various stakeholders across the organisation 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.
• 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.

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