Analytics Engineer — Data Analytics & Transformation (DAT)

Develop and maintain data models and products using SQL and Python to support multiple business domains including Sales, Product, Engineering, Finance, and Commercialization.

Transform business questions into structured analyses with predictive and prescriptive insights to identify trends, risks, and opportunities early.

Own data quality, consistency, and governance while building automated dashboards and self-service data products that replace manual reporting.

2 to 4 years of experience in analytics engineering, data/business analytics, or BI development.

Proficiency in SQL and handling large, complex datasets; hands-on Python skills for analysis and statistical/predictive modeling.

Degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related quantitative field.

Practical experience integrating AI tools in analytics workflows; adherence to software engineering best practices (version control, testing, documentation).

Experienced in applying statistical and predictive methods to business domain problems with methodological rigor.

Capable of translating complex data into clear, actionable business insights understandable by non-technical stakeholders.

Comfortable working in a cross-functional environment collaborating with various business units and using AI tools to increase automation efficiency.