Head of Data Engineering
Lulalend
OVERALL PURPOSE
As the Head of Data Engineering you will be responsible for leading a core team of data engineers and maturing the data engineering competency, leveraging our modern infrastructure to drive tangible business impact. The role is expected to drive the adoption of the best practices and technologies to achieve excellence in data product delivery. You will be accountable for the performance and stability of our production platforms working in collaboration with our engineering and technical operations teams. The ideal candidate will be an experienced data engineering leader with a proven track record of leading high performance teams, fostering a culture of innovation and delivering technical solutions which meet the expected business outcomes. This is a senior management role and will be a key member of the Technology Management team contributing to the execution of the technology strategy at Lula.
KEY RESPONSIBILITIES:
Data Engineering Leadership
- Lead and mentor a high performing Data Engineering team, fostering a culture of delivery and continuous improvement.
- Direct line management of Data Engineers, Analytics Engineers & Machine Learning Engineers.
- Drive quality throughout the systems development lifecycle, ensuring that data engineering principles and best practices are being adhered to resulting in scalable solutions that meet security, performance and programming standards.
- Contribute as a key member of the Technology Management team collaborating with all members to ensure that we deliver a world class experience to our customers.
Strategic Planning and Delivery
- Articulation and delivery of a data strategy which considers the factors of people, process and technology aligned to our technology and business strategies.
- Translate business requirements into technical roadmaps, ensuring that our data infrastructure (Snowflake) is leveraged to support key initiatives such as AI-driven growth and internal platform modernization..
- Research and implement new software technologies that benefit our customers and give us a competitive edge.
- Partner with business stakeholders to understand their data needs.
- Collaborate with Product and Engineering to deliver against all agreed roadmaps.
- Oversee the design, development, and maintenance of scalable data pipelines and infrastructure to support the organization's data needs.
- Report on team activities, and ensure accurate planning and time estimation of data engineering work
- Manage budgets and capacity to support delivery.
- Manage key third party suppliers ensuring they are performing and delivering to SLO’s and SLA’s.
Compliance and Regulatory Oversight
- Stay abreast of relevant data privacy laws, regulations, and industry standards, ensuring the organization's data practices remain compliant.
- Develop and maintain policies and procedures for data handling, access controls, and data retention in accordance with regulatory requirements.
- Work closely with legal and compliance teams to address any data privacy or security issues and drive continuous improvement in compliance practices.
Data Governance
- Establish and maintain a framework for data governance, including data quality standards, metadata management, and data classification.
- Define roles and responsibilities for data stewardship and ensure accountability for data management practices throughout the organization.
- Implement tools and processes to monitor and enforce compliance with data governance policies and standards.
THE EXPERIENCE WE’RE LOOKING FOR:
- Degree in a quantitative field (Mathematics, Computer Science, Engineering, Statistics or equivalent). Masters an added bonus
- 8 - 10 Years + data engineering experience, deep understanding of data management principles, data architecture and ELT processes with hands-on experience in building and managing data pipelines utilising continuous integration
- 3-5 Years experience in a leadership role overseeing data engineering, compliance, and governance functions within a technology-driven organization (advantageous)
- In depth experience of building and supporting high performing/scaling cloud based data platforms
- Proven track record of leading successful migrations of key components within the data stack, ensuring minimal disruption and optimal performance.
- Experience in deploying operational embedded data products for business process efficiencies through data activation and ML Ops
- Demonstrated experience collaborating with embedded analysts through data mesh or lakehouse architecture, ensuring analyst empowerment while maintaining standards
- Demonstrable experience working with Azure, Snowflake and DBT (highly advantageous)
- Strong knowledge of data privacy regulations such as POPIA, GDPR, etc., and experience implementing compliance programs to ensure adherence to these regulations.
- Demonstrated expertise in developing and implementing data governance frameworks, including data quality management, metadata management, and data classification.
- Experience working closely with a product team and within an agile environment
- Experience defining and executing on a data strategy (advantageous)
- Financial services and banking experience (advantageous)
Our Tech Stack
- General: Snowflake, Azure, AzureSQL (MSSQL), Postgres
- Data Engineering: Airbyte, Airflow, CDC, Event Streaming (kafka or similar)
- Analytics Engineering: DBT Cloud, DBT Core
- Machine Learning Engineering: Azure ML, Terraform