Lead Software Engineer

About this role

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Skills you'll use

What you'll do

• Deliver end-to-end solutions in the form of cloud-native microservices architecture applications leveraging the latest technologies and the best industry practices
• Design, build, and operate scalable batch and streaming data pipelines (ETL/ELT) to ingest, process, and curate data for operational and analytical use-cases.
• Work with Big Data technologies and patterns (e.g., distributed processing and large-scale datasets) to ensure performance, reliability, and cost efficiency and develop and maintain curated analytics datasets / data products that enable reporting, KPI measurement, and dashboarding for business stakeholders.
• Partner with business analysts and product teams to define metrics, ensure data quality/lineage, and create trusted datasets that power dashboards and self-serve analytics.
• Use domain modelling techniques to allow us to build best in class business products.
• Structure software so that it is easy to understand, test and evolve.
• Build solutions that avoid single points of failure, using scalable architectural patterns and develop secure code so that our customers and ourselves are protected from malicious actors.
• Promptly investigate and fix issues and ensure they do not resurface in the future and make sure our releases happen with zero downtime for our end-users.
• See that our data is written and read in a way that's optimized for our needs and keep an eye on performance, making sure we use the right approach to identify and solve problems.
• Support the products you've built through their entire lifecycle, including in production and during incident management

Who can apply

• Formal training or certification in software engineering concepts and applied professional experience.
• Recent hands-on professional experience as a back-end software engineer.
• Strong Java experience (recent versions).
• Strong testing experience (unit, component, integration, end-to-end, performance, etc.).
• Hands-on data engineering experience building and operating production-grade data pipelines (batch and/or streaming) and integrations.
• Experience with Big Data / distributed processing and large-scale datasets (e.g., Spark/Hadoop ecosystems or equivalent managed services).
• Strong SQL and experience with analytics data modelling (e.g., dimensional/semantic modelling, KPI definitions).
• Experience with data quality controls, observability, and operational support for data pipelines.
• Experience with cloud technologies, distributed systems, RESTful APIs, and web technologies.
• Knowledge of messaging frameworks and experience operating/supporting mission-critical applications, including security considerations.

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