Senior AWS Data Engineer with Databricks & Google Analytics

Description

Job Summary: This role requires expertise in data analysis and engineering, focusing on building scalable solutions and implementing architectural improvements within an AWS environment. Key Highlights: 1. Expertise in AWS (S3, EMR, Athena, Lambda, SQS, Glue, RDS, Redshift, DynamoDB) 2. Experience with Python, Pyspark, Pandas and Databricks 3. Strong understanding of Spark architecture and distributed systems Description: * Experience with Google Analytics (Foundation and Tagging components) * Minimum 5 years of experience with AWS (S3, EMR, Athena, Lambda, SQS, AWS Glue, RDS, Redshift, DynamoDB) * Minimum 3 years of experience with Databricks * Experience developing with Python, PySpark, and Pandas * Understanding of Spark architecture and the features and challenges of distributed architecture * Knowledge of Oracle databases and PL/SQL Desirable: * AWS Certification: Professional or Specialty * Databricks Certification * Documentation of pipelines via code reverse engineering * Mapping of execution flows and dependencies among processes * Assistance in planning data load migrations * Creation of automated analyses to accelerate reverse engineering * Building scalable and resilient data analytics solutions in the AWS environment * Implementing architectural improvements * Gathering business area requirements and documentation * Familiarity with agile methodologies * Aligning corporate IT environments with business needs, industry standards, and best practices * Ability to embed a data-driven culture into daily operations * Capacity to work collaboratively with empathy, active listening, being heard, and strong communication skills 2511130202461749190