Senior Data Engineer

Akaasa Technologies
Atlanta, GA, United States
7 days ago
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Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Training Data Artificial Intelligence Business Analytics Applications ARM Architecture Cloud Computing Data Architecture Information Engineering Data Governance Python (Programming Language) Machine Learning Performance Tuning Microsoft Copilot
+10 more
SQL Databases Data Ingestion Retrieval-Augmented Generation Snowflake Generative AI Agentic-AI Data Layers AI Platforms Data Management Data Pipelines

Job description

Our client is seeking experienced Senior Data Engineers and Mid-Level Data Engineers to join their growing data engineering team. The ideal candidates will have strong expertise in building scalable data pipelines, developing cloud-based data solutions, and preparing enterprise data for AI and advanced analytics use cases. The selected candidates will work closely with business stakeholders, data engineering teams, and AI engineers to transform complex investment and enterprise data into high-quality, scalable, and reusable data products., * Design, build, and maintain scalable data pipelines in Snowflake to support AI, machine learning, and advanced analytics use cases.

  • Develop and manage data ingestion, transformation, and curation processes for investment and enterprise data.
  • Design and implement AI-ready data assets, including semantic views, vectorized datasets, metadata models, and retrieval frameworks.
  • Enable AI-powered solutions such as AI agents, copilots, and Retrieval-Augmented Generation (RAG) applications.
  • Develop data engineering solutions using Snowflake Cortex, SQL, Python, and modern cloud technologies.
  • Ensure data quality, performance optimization, security, governance, and observability across data platforms.
  • Collaborate with business stakeholders and AI engineering teams to convert complex investment data into governed, reusable data products.
  • Support strategic AI initiatives, including CII, Risk AI, Trade Agent, and other enterprise AI platforms.

Requirements

  • Strong hands-on experience in Data Engineering and building scalable data pipelines.
  • Expertise in Snowflake, including data ingestion, transformation, and data modeling.
  • Strong proficiency in SQL and Python.
  • Experience working with modern cloud-based data engineering technologies.
  • Understanding of AI-ready data architecture, semantic layers, vectorized datasets, and RAG frameworks.
  • Knowledge of data quality, performance tuning, security, and data governance.
  • Strong communication and collaboration skills., * Previous experience in the Financial Services / Investment Banking industry is highly preferred.
  • Experience with Snowflake Cortex and AI/ML-related data engineering solutions.
  • Exposure to AI agents, copilots, and RAG-based applications.
  • Experience supporting enterprise-scale AI and analytics platforms.

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