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Job Description About the Role Lula is on a mission to simplify business funding for South African SMEs. We build fast, digital-first fintech tools that make cash flow management seamless so business owners can focus on doing what they love. We’re a fast-growing, tech-driven team that values curiosity, collaboration, and high impact over red tape. Speaking of love, we’re looking for Lulas who love to make a difference to join our team and change the game. Responsibilities We Embrace Curiosity - We continuously seek better ways to deliver value with a solutions-over-problems mindset. We win as One - We collaborate, build strong relationships and value diverse perspectives We’re Driven by Purpose - We are passionate and committed to delivering the best products and services for SMEs We Execute with Ambition - We set ambitious goals, embrace challenges, and deliver with focus and determination. Work as part of a multi-disciplinary data focussed team (Data, Analytics, Machine Learning Engineers) Collaborate with broader data functionality across the business (Analysts, Data Scientists) Develop greenfield projects using our Azure and Snowflake platforms Assemble data sets that meet functional and non-functional business requirements Develop and maintain operational and analytical data systems Create and maintain robust ELT/ETL products for batch, micro-batch and near real-time data pipelines using Airbyte, Event Grid, Azure Data Factory, Kafka or similar tools Follow test-driven development practices Demo work to both technical and non-technical stakeholders Create documentation and training material for the solutions being delivered Guide and mentor senior and junior team members Azure (Functions, databases, blob storage) DBT Snowflake Airflow Airbyte Event Grid Strong hands-on experience with Snowflake, including warehouse/resource management, semi-structured data handling (VARIANT, JSON), and performance/cost optimisation. Experience with dbt (Core or Cloud) - models, tests, macros, snapshots, and documentation generation. Experience using schemachange, Flyway, Liquibase, or a similar tool to manage database change control as code. Proficient in Jinja templating for building dynamic, reusable SQL/config. Advanced working knowledge of SQL (DDL, DML, JSON, XML) and extensive experience managing incremental/batch loading methodologies (CDC, CT, CDC-style watermarking). Proven experience building ingestion pipelines from diverse source types: APIs, flat files, relational/NoSQL databases, Azure Table Storage, and web scraping. Skilled and experienced in the Azure (or AWS/GCP) cloud platform. Advanced understanding of relational data structures, including keys, constraints, and triggers. Experience with performance tuning and optimisation of RDBMS and/or cloud data warehouses. Experience with relational and NoSQL database technologies (MS SQL Server, MongoDB, CosmosDB, etc.). Ability to design and implement conceptual, logical and physical data models that support organisational needs. Solid understanding and experience in data modeling, data management and governance methodologies. Good understanding of data-related frameworks, methodologies, and patterns. Strong analytic skills working with structured, semi-structured and unstructured data sets. Proficiency in Python (preferred), Java, or Scala. Practical experience applying generative AI / LLM tools to engineering or data workflows (e.g. Copilot, ChatGPT, Claude, or similar). Experience implementing CI/CD pipelines through technologies such as GitLab, Azure DevOps, etc. Experience deploying data systems in an Infrastructure-as-Code (IaC) manner, preferably using Terraform. Strong ability to produce high-quality technical documentation as a routine part of delivery. Experience supporting and working with cross-functional teams in a dynamic environment. Communicates effectively with both technical and non-technical stakeholders.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.