Absa Group
Absa Group
Absa Group ir Āfrikas finanšu pakalpojumu uzņēmums, kas darbojas banku, finanšu un finanšu tehnoloģiju jomā. Tā uzņēmējdarbība aptver Botsvānu, Ganu, Keniju, Maurīciju, Mozambiku, Seišelas, Dienvidāfriku, Tanzāniju, Ugandu un Zambiju, turklāt uzņēmumam ir biroji un struktūrvienības arī Ķīnā, Namībijā, Nigērijā, Amerikas Savienotajās Valstīs un Apvienotajā Karalistē. Grupai ir arī tehnoloģiju atbalsta operācijas Čehijā, un tā apkalpo savus tirgus ar skatījumu, kas sniedzas ārpus Āfrikas kontinenta.

Lead Data Engineer - Johannesburg (Hybrid)

Lead data engineering for Absa Group in a hybrid Johannesburg role, shaping enterprise data architecture, pipelines, analytics tooling, and delivery practices.

Apraksts

  • Set enterprise data architecture direction and lead agile design, deployment, implementation, and continuous optimization of data retrieval, storage, and distribution solutions
  • Own data retrieval, storage, processing, and distribution across a business-area data ecosystem
  • Assess customer data needs and define suitable data architectures
  • Understand the technical landscape and its connected or dependent bank-wide architecture
  • Design and deliver data solutions, including architectures and pipelines
  • Lead design-thinking activities and produce solution blueprints and roadmaps
  • Direct end-to-end solution design and implementation throughout the development lifecycle
  • Develop data retrieval, storage, and distribution architectures in test-driven and domain-driven environments
  • Build analytics tools from data pipelines and deliver optimized, documented code and algorithms
  • Create and maintain CI/CD pipelines and deploy applications across multisite production environments
  • Automate operational tasks with Ansible, Chef, and comparable scripting tools
  • Debug source code and enhance product features
  • Assemble complex datasets and manage data pipelines
  • Build infrastructure for high-volume data delivery and resolve scaling challenges
  • Develop data tools for analytics and data science teams
  • Ensure solutions enable self-service, repeatability, testability, scalability, and resilience
  • Support infrastructure that extracts, transforms, and loads data from varied sources
  • Optimize and automate data retrieval, storage, and distribution processes
  • Define and implement quality-assurance routines with QA and CSO
  • Maintain data separation, security, and quality
  • Align solutions with Group Architecture data standards and Group Infrastructure practices
  • Monitor data products and services for performance, optimization, and cost-to-value
  • Keep current with data retrieval, storage, distribution technologies, and global best practices
  • Coach and mentor engineers
  • Conduct peer reviews, testing, and cross-team problem solving
  • Provide technical subject-matter expertise for Product Engineer attraction and recruitment
  • Contribute to the data engineering team’s development and planning
  • Support people change teams with adoption-process design
  • Identify and reduce technical risks before, during, and after deployment
  • Create and maintain application documentation under technical standards and governance frameworks
  • Prepare business cases and solution specifications for governance processes
  • Participate in incident management and disaster recovery activities
  • Deliver work on schedule and within budget
  • Maintain compliance with regulatory requirements, risk-management frameworks, and Absa policies

Prasības

  • Strong understanding of business data needs and demonstrated data subject-matter expertise
  • Advanced expertise in data architecture and data engineering
  • Experience working with relational and NoSQL databases
  • Experience with integration and streaming platforms
  • Experience designing and implementing data retrieval, storage, processing, and distribution solutions
  • Experience developing analytics tools and optimized, documented code and algorithms
  • Experience creating and supporting CI/CD pipelines with Jenkins or comparable tools
  • Experience deploying and managing applications in multisite production environments
  • Experience using Ansible, Chef, or similar automation and scripting technologies
  • Experience assembling large, complex datasets and managing data pipelines
  • Experience solving high-volume data and scaling challenges
  • Experience with QA, data security, data quality, and governance processes
  • Experience with infrastructure standards and practices covering OLA, IaaS, PaaS, SaaS, and containerization
  • Experience monitoring data products and services for performance and cost efficiency
  • Ability to coach and mentor engineers
  • Ability to perform peer reviews, testing, and collaborative problem solving
  • Ability to identify and mitigate technical risks
  • Ability to contribute to incident management and disaster recovery activities
  • Ability to deliver projects on schedule and within budget
  • Knowledge of regulatory requirements, the Enterprise Wide Risk Management Framework, and Absa policies and standards
  • The provided posting does not specify education requirements

Priekšrocības

  • Equal-opportunity employment
  • Commitment to an inclusive workplace
  • Reasonable accommodation during recruitment
  • Preference may be given to candidates from underrepresented designated groups, including people with disabilities

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