Data Engineering Lead

Responsibilities

• Data Architecture
• Design and implement cloud‑based data architecture components that align with enterprise architecture guidelines and business requirements.
• Contribute to the evolution of data architecture by improving existing patterns, pipelines, and platform components.
• Support "as‑is" and "to‑be" architecture documentation for data platforms and integrations.
• Data Engineering & Pipeline Development
• Design, build, and maintain robust data pipelines in cloud data platforms such as Snowflake or Databricks .
• Develop and optimize SQL‑based data transformations to deliver curated, analytics‑ready datasets.
• Ensure data pipelines are reliable, performant, and maintainable through effective error handling, monitoring, and logging.
• Cloud & Infrastructure Development
• Build and maintain data solutions on the cloud, preferably AWS .
• Provision and manage data infrastructure using Infrastructure as Code tools such as CloudFormation or Terraform .
• Design and support business‑critical storage and compute environments following industry best practices.
• Manage complex technical issues related to data platforms and pipelines.
• Data Software & API Development
• Develop and enhance data applications and services by analyzing requirements and implementing effective solutions.
• Build and maintain APIs using Python to support data access, ingestion, and integration with other systems.
• Contribute to continuous improvement of data software through refactoring and performance optimization.
• Databases & Data Modelling
• Work hands‑on with relational databases , including PostgreSQL and Microsoft SQL Server .
• Design and maintain logical and physical data models that support analytics, reporting, and operational workloads.
• Install, configure, and test complex database environments to ensure they meet functional and performance requirements.
• Data Management & Quality
• Manage key components of the data management system, including data quality, consistency, and integrity.
• Apply organizational data standards, governance practices, and compliance requirements in day‑to‑day development.
• Business Requirements & Collaboration
• Elicit and analyze complex business and technical requirements through workshops, document analysis, and stakeholder discussions.
• Translate business needs into practical, scalable data engineering solutions.
• Collaborate closely with analysts, data scientists, and software engineers to deliver end‑to‑end data solutions.
• Security, Compliance & Operations
• Support information security practices by identifying and helping remediate vulnerabilities and data‑related risks.
• Ensure delivered solutions comply with organizational policies, procedures, and relevant regulatory requirements.
• Documentation & Knowledge Sharing
• Create and maintain high‑quality technical documentation for data pipelines, platforms, and integrations.
• Share knowledge and best practices within the team through documentation and peer collaboration.
• Required Skills & Experience
• Degree in Computer Science, Information Technology, or a related field.
• 7+ years of experience in data engineering with a focus on complex data solutions.
• Proven experience building and supporting cloud‑based data architecture , preferably on AWS .
• Hands‑on experience with Infrastructure as Code tools such as CloudFormation or Terraform .
• Strong experience developing data pipelines in Snowflake, Databricks , or similar cloud data platforms.
• Strong SQL skills for data transformation, optimization, and analysis.
• Experience developing APIs using Python .
• Solid hands‑on experience with PostgreSQL and Microsoft SQL Server .
• Strong understanding of data modelling principles and practical application.
• Experience working with large, complex datasets in production environments.
• Ability to clearly communicate technical concepts and collaborate across teams.

Benefits

Additional Information

Let's Write Africa's Story Together! Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this. Job Description The Data Engineering Lead designs, builds, and maintains scalable and reliable data platforms that support data storage, processing, and retrieval in a cloud based environment. This role works hands on with large and complex datasets, developing data pipelines that move and transform data from source systems into cloud data warehouses and analytical platforms. The Data Engineering Lead is a strong individual contributor who applies deep technical expertise to deliver high quality data solutions, collaborates closely with cross functional teams, and supports the evolution of data architecture within established enterprise standards.

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