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Strong Tier-1 brand, popular mid-level Data Engineer title, broad toolset and 5+ years requirement increase candidate competition.
Technical data engineering skills transfer across industries, but specific cloud and data-platform requirements raise fit sensitivity.
Explicit 5+ years requirement and mandatory Databricks, Snowflake, Spark, and AWS skills make filters strict.
Lead a team of engineers building modular, configurable, API-first tools for Consumer Product & Innovation teams.
Coordinate with multiple teams and provide guidance to junior engineers on software engineering projects supporting business objectives.
Develop and support data services and visualization dashboards using modern web frameworks and cloud technologies.
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent professional experience.
5+ years of hands-on data engineering experience with proficiency in SQL, Spark, and Python.
Hands-on experience with Databricks, AWS (Lambda, Step Functions, DynamoDB, Elasticsearch, S3), Snowflake, and Java.
Demonstrated skills in data modeling, ETL development, data streaming, API development (REST/GraphQL), and microservices architecture.
Experienced in cloud-native software engineering within fast-paced, collaborative environments.
Capable of leading engineering teams, coordinating with diverse technology functions, and mentoring junior engineers.
Technical strength spans full stack from backend Java and API development to frontend data visualization frameworks and DevOps practices.