Description

You will build and maintain scalable data architecture and processing pipelines within an AWS environment.

Responsibilities

• Design and implement data pipeline architectures for ingestion, cleansing, and transformation of batch and stream data.
• Build infrastructure for extracting and loading data from diverse sources using SQL and AWS big data technologies.
• Automate manual processes and optimize data delivery to improve system scalability.
• Develop analytics tools and datasets to support product optimization and business performance metrics.
• Collaborate with Product, Data, and Design teams to resolve technical issues and support infrastructure needs.

Required Skills

• 6+ years of experience in a Data Engineering role.
• Hands-on experience with AWS services including EMR, Redshift, Athena, Glue, and Lambda.
• Proficiency in Python for serverless development and data processing.
• Experience with streaming and messaging technologies such as Kafka or Kinesis.
• Strong knowledge of relational and NoSQL databases including PostgreSQL, Aurora, RDS, and DynamoDB.
• Expertise in Spark for large-scale data processing.
• Proven ability to manage data lakes and complex ETL/ELT workflows.
• Bachelor's degree in Computer Science, Statistics, Informatics, Information Systems, or a quantitative field.

Key Skills

Education

Bachelor's degree