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Strong employer brand plus broad data and engineering skillset yields moderate competitive density.
Specialized cloud data platform skills increase domain specificity but remain reasonably transferable across industries.
Explicit 8+ years and required Databricks/Spark/Snowflake/AWS expertise and leadership make shortlisting highly strict.
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Lead and coordinate a team of engineers to build modular, configurable API-First data tooling for the Consumer Product & Innovation team.
Develop and maintain data engineering solutions including SQL, Spark, Python, and cloud-native services on AWS and Databricks.
Provide technical guidance and coaching to junior team members and collaborate cross-functionally with other teams in Global Technology.
Bachelor’s degree in Computer Science, Engineering, Information Systems or equivalent experience.
8+ years of hands-on data engineering experience with expertise in SQL, Spark, Python.
Proficiency with Databricks, AWS (Lambda, Step Functions, DynamoDB, Elasticsearch, S3), Snowflake, and Java.
Experienced in API development (REST/GraphQL), microservices, data modeling, ETL, data streaming, and CI/CD with DevOps responsibilities.
Experienced leader capable of managing and mentoring engineering teams in a collaborative, fast-paced environment.
Strong cloud-native software engineering background, particularly with AWS and Databricks ecosystems.
Technically versatile engineer comfortable with both backend services (Java, microservices, APIs) and frontend data visualization frameworks (React, Vue.js, Angular).