Senior Analytics Engineer

at  Lula

WHAT WE DO

Lula is an innovative and human-focused FinTech company on a mission to help small businesses optimise their cash flow. Our purpose is to help SMEs manage their businesses better, faster, and more simply, so they can spend more time doing what they love.
If you’re looking for a new place to call ‘home’ that believes in the potential of the broader SME landscape in South Africa and a place where you’ll work with awesome people - then Lula’s the place for you!

THE SKILLS AND EXPERIENCE WE’RE LOOKING FOR

• Bachelor’s degree in computer science, mathematics, statistics, or relevant experience in related field
• 6+ years of experience in data engineering, data warehousing, or a related field
• Strong programming skills in Python, SQL, and/or Go
• Experience with cloud-based data platforms, such as AWS, Azure, or Google Cloud
• Familiarity with data modelling, data warehousing, and data pipeline design
• Experience with big data technologies, such as Hadoop and Spark
• Strong understanding of data structures, algorithms, and software engineering principles
• Experience with DBT (Data Build Tool) and BI tools like Hex / Tableau / Looker
• Excellent problem-solving skills
• Strong communication skills and ability to collaborate with cross-functional teams

OVERALL PURPOSE

We are looking for a Senior Analytics Engineer to join our team. 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 bugs and performance issues are quickly identified.
As a member of the Data team, your primary focus will be to combine raw information from different sources to create consistent and consumption-ready formats. More specifically, you will need to construct and test architectures that enable data extraction and transformation for predictive or prescriptive modelling.

RESPONSIBILITIES WILL INCLUDE (BUT IS NOT LIMITED TO):

• Leading the development and design of data architecture strategies that align with business goals and objectives.
• Providing guidance and mentorship to junior data engineers, helping them grow and develop their skills.
• Developing and maintaining relationships with stakeholders across the organisation, including data scientists, analysts, business leaders and third party stakeholders.
• Evaluating new technologies and tools that can improve data processing and analysis, and making recommendations on their adoption.
• Taking ownership of large-scale data engineering projects, managing timelines and budgets, and ensuring successful project delivery.
• Ensuring compliance with data privacy and security regulations, and implementing data governance policies and procedures.
• Collaborating with cross-functional teams to identify data-related challenges and opportunities, and develop solutions that meet the needs of the business.
• Driving the adoption of best practices for data quality, reliability, and performance.
• Continuously improving data pipelines and systems, and identifying opportunities for automation and optimisation.
• Developing and implementing disaster recovery and business continuity plans for data infrastructure.