Data Engineer
Alpharetta, GA – Hybrid (F2F Interview)
Capgemini/Morgan Stanley
Long Term
Note: Only W2
Job Description:
We are seeking a Senior Data Engineer to support data platforms and analytics enablement for enterprise scale digital and AI initiatives, including Agent Desktop and Service Assist AI ecosystems. The role focuses on building and operating scalable data pipelines, search optimized data stores, and cloud data warehouses using Elastic DB, SQL, ETL frameworks, and Snowflake.
The candidate is expected to have Strong hands on execution capability, production support maturity, and experience working in regulated, enterprise environments.
The candidate is expected to have Strong hands on execution capability, production support maturity, and experience working in regulated, enterprise environments.
Must Have :
• 8–10 years of hands on experience in data engineering or data platform roles.
• Strong expertise with Elastic DB / Elasticsearch for indexing, search, and analytics use cases.
• Advanced SQL skills with experience tuning complex queries.
• Strong experience with Snowflake architecture, data modeling, and performance optimization.
• Hands on experience building ETL / ELT pipelines using industry standard tools or custom frameworks.
• Proficiency in Python and/or scripting for data processing and automation.
• Core Banking or Financial/Wealth management domain working experience required
• 8–10 years of hands on experience in data engineering or data platform roles.
• Strong expertise with Elastic DB / Elasticsearch for indexing, search, and analytics use cases.
• Advanced SQL skills with experience tuning complex queries.
• Strong experience with Snowflake architecture, data modeling, and performance optimization.
• Hands on experience building ETL / ELT pipelines using industry standard tools or custom frameworks.
• Proficiency in Python and/or scripting for data processing and automation.
• Core Banking or Financial/Wealth management domain working experience required
Good to Have
• Experience supporting AI/ML, analytics, or digital assistant platforms.
• Exposure to streaming or near real time data processing.
• Experience working in financial services or other regulated environments.
• Snowflake, Elastic, or cloud platform certifications.
• Experience supporting AI/ML, analytics, or digital assistant platforms.
• Exposure to streaming or near real time data processing.
• Experience working in financial services or other regulated environments.
• Snowflake, Elastic, or cloud platform certifications.
