Sr. Data Engineer

Business overview:

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.

Role overview:

As a Sr. Data Engineer, you’ll drive the design, development, and optimization of our data engineering pipelines and services with a strong software engineering mindset.

You'll also play a pivotal role in fostering growth and collaboration within the team, mentoring junior colleagues, and refining processes to help us maintain excellence.

If you’re excited to make a lasting impact both technically and as a team leader, we’d love to meet you.

Desired skills:

• A university degree from a reputed University with a record of academic excellence in Mathematics, Computer Science, Engineering, Physics or similar.
• 8+ years of relevant experience in Data Engineering, warehousing, ETL, automation, big data and cloud technologies, etc.
• Ability to write clean, scalable, maintainable code in Python. Has 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 and orchestration such tools as Apache Airflow and Nifi.

  • Large Scale/ Big Data technology, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka.

  • Workflow orchestration tools like Apache Airflow.

  • Containerisation with Docker, deployment on Kubernetes.

  • NoSql and graph databases.

  • Unix server administration and shell scripting.
• Experience in building scalable data pipelines for highly unstructured data.
• Experience in building DWH and data lakes architectures.
• Experience in working in cross-functional team 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.
• Capitalise 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.