Working for a top financial services company, the Lead Data Engineer will be responsible for creating business value by leading a dynamic team that applies data engineering and data management disciplines to design and build data solutions that enable data driven decision support, in order to optimize business decisions and processes.
Key Performance Areas:
1. Data Solutions
- Sourcing data
- Identify data sources that can add value to decision making.
- Work with source system owners and analysts to understand source data, e.g. data profiling, definition and mapping.
- Design and implement efficient data loads, using traditional structured data ETL techniques.
- Design and implement real time and near real time data load solutions, using technologies like data streaming.
- Design and implement unstructured data loads, e.g. text speech, images and video.
- Design and implement load monitoring tools and procedures and perform continuous monitoring and optimising of loads.
- Work with analysts and architect to design and implement effective and efficient data warehouse data models using appropriate modelling techniques.
- Design and implement data pipelines for ad hoc, unstructured and other data models.
- Enhancing data
- Design and implement appropriate aggregation data structures that enhance usability of data, e.g. multi-dimensional OLAP structures, summary tables etc.
- Design, implement and maintain appropriate indexing on tables to enhance speed of access.
- Design and implement data models that support automated decision making and/or further analytics.
- Continuously search for data elements from other sources to enhance existing data objects to supplement / enhance context.
- Design and implement data monitoring solutions and procedures and continuously monitor and maintain integrity of existing environment, troubleshoot technical and data issues and make appropriate changes where required.
- Design and implement meta-data solutions that assist with understanding and managing data.
- Work together with business owners, analysts and IT to manage changes to data in the organization and maintain good data governance.
- Provide technical and data related support to source system teams and external parties with whom we exchange data.
- Manage data growth and usage by implementing effective strategies, e.g. archiving and indexing.
- Manage systems, technology and tools that enable data management and analytics and liaise with IT infrastructure and IT Operations regarding system and infrastructure management.
2. Personal, People and Functional leadership
- Take ownership of own work by delivering high quality work on time.
- Show initiative and be pre-active in finding opportunities to improve data and/or processes.
- Take ownership of own career development by continuously improving skills, knowledge and the application thereof in designing and implementing solutions.
- Positive engagement in team activities and actively contribute ideas to improve team dynamics and performance.
- Cross functional data and team knowledge gathering and sharing.
- Responsible for team activities, team dynamics and performance.
- Manage project and task delivery of team as well as quality control there off.
- Data analysis
- Data visualisation
- Data modelling
- Microsoft business intelligence data technologies (SSIS, SSAS, SQL Server)
- Data warehouse concepts and best practices
- Degree in information technology / mathematics / engineering / actuarial science or related discipline.