Senior Data Engineer

Quick Facts

• Role: Senior Data Engineer

• Work focus: Build, optimize, and operate a central enterprise Smart Data Platform and develop data products in a Data Mesh approach

• Team setup: Agile, cross-functional squad with data, actuarial, modeling, and product stakeholders

Description

You will help shape and run AXA’s modern data landscape by creating and improving ETL/ELT pipelines and foundational data models for enterprise data products. Working closely with users of data products and core insurance business stakeholders, you will implement those products on the Smart Data Platform using a Data Mesh approach. You will also support the team in using modern development technologies and pragmatically evaluate and evolve dbt-based workflows and other technologies.

Responsibilities

• Contribute to the build, optimization, and operation of the Smart Data Platform (central group-wide data platform)

• Develop data products with business and data stakeholders in an agile, interdisciplinary squad and implement them in a Data Mesh approach

• Create high-quality ETL pipelines, integrate multiple data sources, and establish baseline data models

• Support the team’s adoption and usage of modern development technologies and methods such as Snowflake, AWS, and dbt

• Bring in new ideas, question the status quo regularly, and drive topics proactively

• Actively shape the data landscape and take early ownership and decision-making responsibility

Requirements

• Completed degree in Informatics, Business Informatics, Data Science, Statistics, Mathematics, or a comparable quantitative program

• At least 3 years of professional experience as a Data Engineer, including knowledge of Snowflake, AWS, dbt, SQL, and building ETL/ELT pipelines

• Analytical mindset and ability to structure and solve complex data and pipeline problems with robust solutions

• Strong teamwork skills and ability to reconcile different viewpoints into viable decisions

• Good understanding of data structures, data quality, and data modeling; willingness to get up to speed with complex data landscapes and technologies such as Data Vault 2.0 and bitemporal historization alongside dbt

• Communication skills to convey technical and domain context appropriately and bring together stakeholders such as actuaries, modeling experts, and Product Owners

• Motivation to question existing solutions, identify improvement opportunities, and pragmatically assess and advance new technologies and dbt-based workflows

Benefits

• Modern data landscape with flat hierarchies

• Flexible working hours within a 38-hour week with flextime

• 30 vacation days, plus Christmas and New Year’s Eve off

• 60% home office and possibility to work mobile from abroad

• Fair compensation, company pension plan, and employer-provided benefits for savings/investment

• Diverse learning and development opportunities