AWS Hands-on Solutions & Data Architect:
Overview: Combination of AWS Architect + Analyst + Engineer + Lead role
Core Workload / Tech stack Skills & Experience: AWS Lambda, AWS S3, AWS IoT Core, Kafka, AWS Kinesis, Data Analysis
Secondary Workload / Tech stack Experience: Databricks, Snowflake
Domain: Media - TV/Set Top Box/Customer Premise Equipment
MUST:
Media domain
AWS, Databricks (PySpark) and Snowflake skillset someone who has extensively created data/ETL pipelines
Required Skills:
Strong Systems and Architecture Analysis Experience
Strong hands-on Experience architecting Event driven architectures.
Microservices experience is required by secondary to Event Driven
Hands on experience implementing AWS Lambda functions
Hands on experience with streaming and IoT data and datasets
Hands on implementation experience on Kafka, Kafka topics
Prefer experience migrating Kafka topics to AWS Lambda and AWS Kinesis
Strong data warehousing / data lake background
Led a team of 15+ data engineers
Analysis of streaming data, data pipelines, connected events
Implement AWS architecture best practices, standards and guidelines for data streaming
Re-engineer Kafka Topics to AWS IoT Core/AWS Kinesis/S3/AWS Lambda
Excellent communication skills to help Data Engineering team understand the event correlation and appropriate Data Engineering modification needs and contextualization
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Last updated on Sep 7, 2023