Job Description & Details
This is a heavy-hitting AWS Data Architect role based in Alameda, requiring deep expertise in cloud-native data platforms and enterprise integrations. You will be calling the shots on complex data lakehouse designs while bridging the gap between raw AWS infrastructure and Salesforce data ecosystems.
What You'll Actually Be Doing
Your days will be split between high-level architectural planning and getting your hands dirty with large-scale data pipelines. You'll spend significant time designing and optimizing S3, Glue, Redshift, and EMR implementations while making sure Salesforce data flows seamlessly into your analytics environment. Expect to handle complex data modeling challenges, review code from your engineering team, and troubleshoot performance bottlenecks across distributed systems.
The Core Tech Stack
You absolutely must know the AWS data stack inside and out—specifically S3, Redshift, Athena, Glue, and Lake Formation. Beyond that, the company relies heavily on Python/PySpark for ETL processing, advanced SQL for query optimization, and Tableau for the BI visualization layer. Since Salesforce integration is a major pillar here, solid experience pulling data out of Sales and Service Cloud via APIs or middleware is non-negotiable.
Interview Expectations
Expect the hiring team to grill you on how you would design a multi-tenant, secure data lakehouse from scratch while maintaining strict IAM policies and data masking standards. They want to see how you balance performance optimization with cost management in Redshift or EMR. When answering architectural scenario questions, focus heavily on trade-offs between batch and real-time streaming, and explain how you ensure data quality before it hits the Tableau semantic layer.
Application Advice
Make sure your resume doesn't just list technologies, but explicitly highlights your leadership and end-to-end data platform implementations. Weave in keywords like dimensional modeling, AWS Glue, PySpark, Tableau performance tuning, and Salesforce data integration naturally throughout your work history to easily clear the automated ATS filters.