Associate Technical Architect - Data

Basic Qualifications

• 8+ years of experience in designing and implementing data warehouses and data lakes/lakehouses on AWS.
• Proven success working with globally distributed teams in collaborative delivery environments.
• Deep working knowledge across key AWS Data & Analytics services, including:
• Building large-scale data lake architectures on Amazon S3 and open table formats
• Implementing governance and cataloging through AWS Lake Formation.
• Developing ETL and metadata frameworks using AWS Glue.
• Leveraging AWS Lambda for serverless data processing.
• Running distributed data workloads on Amazon EMR.
• Enabling real-time data pipelines with AWS Kinesis (Data Streams and Firehose).
• Orchestrating pipelines using AWS Step Functions/Amazon MWAA/similar services.
• Designing and optimizing schemas and query performance on Amazon Redshift, including Spectrum and Serverless features.
• Querying large datasets interactively using Amazon Athena.
• Managing operational databases using Amazon RDS across engines such as PostgreSQL, MySQL, and Aurora.
• Integrating and migrating data using AWS DMS, Glue Connectors, EventBridge, SNS, and SQS.
• Strong programming capability in Python and PySpark for large-scale data processing.
• Proficiency in writing complex SQL queries, analytical functions, and performance tuning for large datasets.
• Familiarity with NoSQL databases such as Amazon DynamoDB, MongoDB, or DocumentDB.
• Strong understanding of partitioning, indexing, scaling approaches, and query optimization techniques.
• Proven experience in architecting and implementing data pipelines using native AWS services in a modular and resilient manner.
• Solid understanding of data modeling concepts, including dimensional, normalized, and lakehouse patterns.
• Background legacy/on premise to AWS migration engagements.
• Solution Architect- Associate or Data Engineer- Associate Certification.