Description

You will lead the design, build, test, and deployment of data components while providing technical direction to the engineering team.

Responsibilities

• Lead the design and implementation of data quality check methods and ensure test-driven development.
• Define technical scope and lead the delivery of solutions based on specific use cases.
• Own data security and permission solutions, including encryption, user access controls, and logging.
• Establish technical standards and guidelines that meet compliance and auditing requirements.

Required Skills

• 10+ years of experience with the AWS Tech Stack and Python for large volume data processing.
• 8+ years of experience in AWS Data Engineering.
• 8+ years with Terraform Enterprise.
• 7+ years of experience with AWS Lakeformation.
• 5+ years of experience with AWS EMR, Apache Hudi, AWS Redshift, and SageMaker/ML.
• 3+ years of experience with Flink.
• Strong proficiency in SQL and experience with Aurora, PostgreSQL, DynamoDB, and RDS.
• Deep knowledge of AWS Glue (Catalog, ETL, Crawler), Athena, Lambda, and S3 storage concepts.
• Experience implementing and tuning streaming use cases within the Big Data ecosystem (Spark, Kafka, Kinesis).

Preferred Skills

• Experience with AWS CloudTrail, SNS, SQS, CloudWatch, Step Functions, and OpenSearch.
• Knowledge of DevOps pipelines (Bitbucket, Concourse) and Secrets Management (Vault, AWS Secrets Manager).

Key Skills

Education

ANY GRADUATE