Job Description

Essential functions-
Actively look for opportunities to select the most suitable and feasible solutions that collect, manage, and convert raw data into usable information, share expert technical knowledge and skills to improve skills of the team and improve cost efficiency of data engineering activities.
Apply thought leadership in steering the data traceability standards, guidelines and processes to ensure data quality, keeping track of data sources and setting up appropriate data version control processes and systems ensuring alignment to defined data architecture.
Assess the impact of privacy and other legislation on the data landscape and ensure compliance with data governance and data security requirements.
Build and maintain close relationships with data consumers and guide them in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
Coach, guide and mentor less experienced Data Engineers on technical aspects of the design, build, operationalising, securing and monitoring of data pipelines and data stores as well as on engaging effectively with relevant stakeholders, sharing expert knowledge and skill.
Collaborate with technology colleagues and segment/country data teams to understand viable data solutions and apply subject matter expertise in recommending the best solutions within architectural guidelines.
Continuously analyse data to direct teams to identify and recommend optimisation and improvements to enable proactive analysis and evaluation of the databases.
Develop, construct, and maintain complete data architecture, thus making data accessible for downstream use case consumption and allowing for data-led and data driven decision making.
Direct decisions relating to data engineering and data integration. Educate internal stakeholders on data engineering and data integration perspectives on new approaches.
Direct teams to create data tooling enabling data consumers in building and optimising data consumption, taking integration and usage patterns into account.
Direct the design, documentation and implementation of processes for executing partner system alignments, communicating these with the relevant stakeholders including Governance. Steer teams towards continually enhancing processes to deal with the dynamics of partner systems alignment.
Direct the execution of internal and external data migrations across different and multiple databases, applications, servers and ensure data stores are defined and implemented based on system requirements and business consumer requirements
Drive automation initiatives and guide teams to identify, design, and implement internal process improvements, automating manual processes, optimising data delivery, re-designing infrastructure for greater scalability, etc.
Drive the achievement of a data driven culture through coaching, mentoring and motivating the data consumer community and convert staff into data citizens through education and awareness initiatives to support data-led decision making.
Engage with Data Engineering leads and communicate any concerns, issues, risks and progress regarding work output to enable a culture of continuous development and learning and guide the leads in issue and risk resolution.
Execute against data strategy and data vision, leading the assessment and selection of suitable approaches establishing their relevance and feasibility, advising on the evaluation and impact analysis of major design options, realising the strategy into applicable data solutions.
Guide insights teams, Technology engineers and Data & Analytics leadership in identifying opportunities for process improvements, recommend system modifications and shape the development of policies for data governance.
Guide teams in interpreting business requirements, defining and providing technology solutions that collect, manage, and convert raw data into usable information to be interpreted by data consumers and insights teams. Steer the deployment of solutions in accordance with applicable architecture, solution designs, standards, policies and governance requirements.
Lead the identification of complex, often abstract problems that extend across multiple business lines, functions, applications, data bases and servers through engagements with senior leaders and apply a creative approach to solving the problems which will address both technical and people or culture challenges simultaneously.
Lead, guide and shape the identification, design and implementation of internal process improvements including re-designing infrastructure for greater scalability, optimising data delivery, and automate manual processes.
Oversee and guide the execution on the design, definition and development of Application Programming Interfaces (API's), aligning to relevant frameworks and guidelines.
Oversee the application and implementation of data integration, warehousing and reporting best practices, ensuring applicable standards are adhered to in the solution design.
Own, and is accountable for, a large application platform or a collection of application platforms that deliver a capability/ service and take full accountability for the build, creation, management, and optimisation of multiple data pipelines, moving data pipelines into production.
Partner with Information security teams to safeguard and ensure compliance with data governance and data security requirements while directing teams to create, improve and operationalise integrated and reusable data pipelines.
Review data capability levels and collaborate with stakeholders to develop plans to achieve desired capability state. Facilitate knowledge sharing through various structures to strengthen capacity and promote best practice.
Steer teams in acquiring datasets that align with business needs and requirements to enable useful and actionable information, guide teams in providing feedback on the clarity and completeness of data requirements.
Steer the build of required infrastructure for optimal extraction, transformation and loading of data from various and multiple data sources using various technologies.
Vigorously oversee and drive alignment to data transfer/data protection and information risk policy implementation, ensuring compliance to relevant legislation and internal standards and governance requirements.
Qualifications & Experience required-

• Business Commerce, Information Studies, Information Technology Degree

8-10 years building databases, warehouses, reporting and data integration solutions, optimise big data data-pipelines, architectures and data sets. Create and integrate APIs. Perform root cause analysis on internal and external data and processes and identify opportunities for improvement. Work with data science teams to refine and optimise data science and machine learning models,algorithms. Work with IT and business while integrating analytics and data science output into business processes and workflows.
8-10 years advanced experience in working with large, heterogeneous datasets in building and optimising data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. Knowledge of integration patterns, styles, protocols and systems theory
10 years plus - Database programming languages ie SQL, PL/SQL, SPARK and or appropriate data tooling, data pipeline and workflow management tools. Work across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems and through containerisation techniques. Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data consumers.

• Preference will be given to candidates with experience in financial services organisations.

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