About the Role
AXA XL recognizes digital, data and information assets are critical for the business, both in terms of managing risk and enabling new business opportunities. Data Science and Applied AI assets should not only be high quality, but also drive a sustained competitive advantage and delivering a superior experience to our internal, external customers and improving efficiency. Our Innovation, Data and Analytics function is focused on driving innovation by optimizing how we leverage digital, data and AI to drive strategy and differentiate ourselves from the competition.
As we develop an enterprise-wide data and digital strategy that moves us toward greater focus on the use of data and strengthen our digital, AI capabilities, we are seeking an Engineering Manager / Senior Engineering Manager for Data and ML applications.
In this role you will be accountable for developer success in adopting engineering best practice and enterprise standards across the value chain of data science applications – from data engineering to ML operations (training, serving, monitoring), and microservice / web application engineering.
Our tech stack: Azure Data Lake, Azure Databricks (Notebooks, APIs, Workflows), MLflow, dbt, Harness CI/CD, OpenShift, Docker, GitHub, JIRA
What will your essential responsibilities include?
- Set engineering standards and be accountable for their adoption in data, ML and microservice app developers. Ascertain sub-linear scalability (resource, cost, headcount) of ML and data operations as inventory of live critical application grows.
- Interface and proactively collaborate with colleagues in Data Ops, Platforms, Infrastructure to ensure developer and ops productivity and experience is optimised. Help shape priorities for Ops and Platforms teams.
- Partner with Product Owners and Scrum master’s to participate in sprint planning, structure tickets and defining ‘done’ when it comes to engineering user stories / tasks.
- Serve as a go-to escalation point for complex engineering tasks or decisions.
- Manage group of 4 engineers: 2 in the UK and 2 in India (data, ML, DevOps), and mentor other engineering populations as required.
In this role, you will report to the Division Lead, Data Science Platforms.
We’re looking for someone who has these abilities and skills:
- Senior Engineering professional with recent hands-on skills in designing, building, and optimizing scalable cost-efficient data systems and applications in a cloud-first environment.
- First-hand deep expertise in engineering ways of working such as CI/CD, release lifecycle, data observability, data testing, continuous model validation with tangible track record of instituting change.
- Software development experience in Python, or Scala. Familiarity with all, and expert in some of the below: SQL, Databricks or Spark, data warehousing, feature store design, Kubernetes, orchestration tools, monitoring tools, IaC, Docker, data streaming technologies.
- Substantial experience as a Data Engineer / Software Engineer / ML Engineer on an open-source tech stack with Python, Scala, Spark, ‘modern data’ platforms such as Databricks, Snowflake etc., cloud platforms, database technologies.
- Track record of leading and motivating high performance engineering staff through ‘leading by example’ hands-on approach.
Senior EM Would Have The Following
- Clear observable track record of success in ML application development and management in a medium to large organization.
- First-hand expertise in developing scalable and secure applications for deployment on Kubernetes, using data streaming technologies.
- Experienced people manager and senior stakeholder communicator with mature style.