Data Engineer II

Summary:

The Data Engineer role is focused on designing and developing data migration pipelines and data models to support analytics and AI-native applications. This position involves working with AWS tools and collaborating with cross-functional teams to ensure successful data transitions and operational excellence.

Responsibilities:

• Architecture & Migration: Design and develop end-to-end data migration pipelines using AWS (S3, Glue, Redshift, Lambda) and internal data tools to transition data from legacy CRM systems to Salesforce.
• Pipeline Engineering: Build scalable, maintainable pipelines for both structured and unstructured data, ensuring high performance for batch processing.
• Data Modeling: Design and implement optimized data models within Redshift and Salesforce to support analytics and downstream AI-native applications.
• Cross-Functional Collaboration: Partner with Software Developers, BIEs, and Product Managers to gather functional requirements and translate them into technical specifications.
• Operational Excellence: Implement automated monitoring, data quality checks, and error-handling frameworks to ensure 100% data accuracy during the migration lifecycle.

Requirements:

• 3 years of professional experience in Data Engineering, specifically focusing on large-scale migrations.

Required Skills:

• Proven ability to write complex SQL, highly optimized queries, and perform deep-dive data analysis.
• Hands-on experience with AWS Redshift, S3, Glue, and Lambda.
• Proficiency in Python (preferred) or Java/Scala for data manipulation and automation.
• Experience with modern ETL frameworks and legacy tools (e.g., Informatica, SSIS) to facilitate reverse engineering of undocumented legacy systems.
• Strong understanding of dimensional modeling, Star/Snowflake schemas, and data warehousing best practices.

Preferred Skills:

• Direct experience with Salesforce Data Loader, Bulk API, and architecting data flows between AWS and Salesforce.
• Experience with QuickSight or Tableau to build validation dashboards that track migration progress and data parity.
• Demonstrated success in reverse-engineering legacy analytical applications where documentation is sparse.
• Experience in building AI agents to perform code refactoring and code migrations.

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