Galytix (GX) is delivering on the promise of AI.
GX has built specialised knowledge AI assistants for the banking and insurance industry. Our assistants are fed by sector-specific data and knowledge and easily adaptable through ontology layers to reflect institution-specific rules.
GX AI assistants are designed for Individual Investors, Credit and Claims professionals. Our assistants are being used right now in global financial institutions. Proven, trusted, non-hallucinating, our assistants are empowering financial professionals and delivering 10x improvements by supporting them in their day-to-day tasks.
Responsibilities:
- Helping to architect, design, implement, and optimise our data ingestion, transformation, and spreading pipelines and processes.
- Developing data models, processing pipelines, and back-end services supporting the data science teams, automating processes, building integrations, and analytics.
Desired skills:
- A university degree in Mathematics, Computer Science, Engineering, Physics or similar.
- 5+ years of relevant experience in Data Engineering, warehousing, ETL, automation, cloud technologies, or Software Engineering in data related areas.
- Ability to write clean, scalable, maintainable code in Python with a good understanding of software engineering concepts and patterns. Proficiency in other languages like Scala, Java, C , C are an advantage.
- Proven record of building and maintaining data pipelines deployed in at least one of the big 3 cloud ML stacks (AWS, Azure, GCP).
- Hands-on experience with open-source ETL, and data pipeline orchestration tools such as Apache Airflow and Nifi.
- Experience with large scale/Big Data technologies, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka.
- Experience with workflow orchestration tools like Apache Airflow.
- Experience with containerisation using Docker and deployment on Kubernetes.
- Experience with NoSQL and graph databases.
- Unix server administration and shell scripting experience.
- Experience in building scalable data pipelines for highly unstructured data.
- Experience in building DWH and data lakes architectures.
- Experience in working in cross-functional teams with software engineers, data scientists, and machine learning engineers.
- Experience in working with or leading an off-shore team.
- Proven record of building data science environments deploying ML solutions in at least one of the big 3 cloud ML stacks (Azure/AWS/GCP) and on Kubernetes clusters.
- Excellent written and verbal command of English.
- Strong problem-solving, analytical, and quantitative skills.
- A professional attitude and service orientation with the ability to work with our international teams.
Why you do not want to miss this career opportunity?
- We are a mission-driven firm that is revolutionising the Insurance and Banking industry. We are not aiming to incrementally push the current boundaries; we redefine them.
- Customer-centric organisation with innovation at the core of everything we do.
- Capitalize on an unparalleled career progression opportunity.
- Work closely with senior leaders who have individually served several CEOs in Fortune 100 companies globally.
- Develop highly valued skills and build connections in the industry by working with top-tier Insurance and Banking clients on their mission-critical problems and deploying solutions integrated into their day-to-day workflows and processes.