Data Engineer Lead
Cape Town, South Africa
3d ago


Lulalend is a FinTech company with a belief in the power of small business. We work hard to empower businesses across South Africa with the funds they need to grow.

Small business owners are the foundation for growth in our economy, and they deserve an easy and inspiring lending process.

Lulalend was founded because there is an underserved market for access to funding that the banks and other lenders overlook.

We innovate in order to significantly reduce this credit gap - directly assisting our economy and job creation on a grand scale.

So, by joining our team you're helping businesses stay open, grow and offer more job opportunities. Yay you!

Lulalend is a one of a kind business literally. There is no-one in South Africa doing what we're doing yet, because we're awesome!

At Lulalend we :

  • Are passionate about helping SMEs succeed
  • Believe in responsible lending
  • Strive to offer an unbeatable customer experience
  • Value humility and teachability
  • Embrace technology
  • Communicate openly
  • Work hard and play hard

    Our Data Engineer Lead role calls for an individual who champions the data journey and has demonstrated an ability to lead and mentor junior team members.

    Not only will you need to be very strong technically applying a hands-on approach but you'll be passionate about helping others grow.

    You will be tasked with implementing and maintaining data models with the goal of improving data reliability and quality, ensuring scalable data pipelines are working smoothly, and performance issues are quickly identified.

    Working closely with our Head of Data Science, you will ensure accurate, on-time data delivery, helping us make smarter decisions to deliver even better products.

    Responsibilities will include :

  • Develop, maintain and ensure utmost quality of our Data Warehouse and Data Lake
  • Develop and maintain scalable data pipelines and systems
  • Monitor production runs to ensure accuracy and on-time delivery of data
  • Provide input around how we can improve tools and processes already in place
  • Drive best practice around data collection, sharing knowledge and guidance with junior team members
  • Collaborate with our Product team to ensure data engineering work is prioritised across our team of Data Scientists so that quality delivery is ensured
  • Identify opportunities for data acquisition that is relevant for building analytical systems
  • When required, build out new API integrations to support continuing increases in data volume and complexity
  • Build and maintain API's hosted by the Data Science team, ensuring 99.9% uptime
  • Co-ordinate and produce bespoke data sets for consumption by machine learning algorithms
  • Explore ways to enhance data quality and reliability
  • Process, cleanse, and verify the integrity of data used for analysis
  • Conduct analyses and present results in a clear manner
  • Refactor code in order to maintain neatness in the repos
  • Write unit / integration tests
  • Contribute to data engineering wiki, and document work
  • Improve deployment processes for the Data Science team
  • Drive best practice around data engineering, share knowledge and provide guidance to junior team members
  • Participate in the recruitment process when we look to expand our team

  • Strong team leadership skills
  • Data-oriented
  • Big picture thinker
  • Excellent collaboration skills
  • Hands-on mentality
  • Influencing skills
  • Strong problem-solver
  • Focused on high quality output
  • Self-starter

  • Degree in a quantitative field (Mathematics, Computer Science, Engineering, Statistics or equivalent), preferably a Masters qualification
  • Data engineering certification (e.g. Microsoft Certified Azure Data Engineer) an added bonus
  • Proven track record of 4+ years in a data engineering role
  • Expert in SQL and Python with experience in PostgreSQL / MS SQL
  • Deep understanding of schema design and data modelling
  • Experience in scaling and enhancing data capabilities, workflows, and reporting
  • Experience with source code and version control
  • Experience with data visualisation tools
  • Decent knowledge of cloud platforms and functionality, particularly Azure Blob Storage, Data Factory, etc.
  • Go-to-person in the team, experience leading / mentoring other team-members to get teams working together to solve problems
  • Proven role-model, leading by example and always demonstrating best practises
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