Data Engineer - Snowflake, Python, AWS & AI

We are seeking a skilled Data Engineer to design, develop, and support modern data platforms and pipelines that power analytics, reporting, and AI-driven solutions. The ideal candidate will have strong expertise in Snowflake, Python, SQL, AWS, Oracle, and Apache Airflow, with exposure to AI/Generative AI technologies., * Design, build, and maintain scalable ETL/ELT data pipelines using Python and SQL.

• Develop and optimize data solutions in Snowflake, including data modeling, performance tuning, and automation. Integrate and transform data from Oracle, APIs, AWS services, and other enterprise systems.
• Build and manage workflow orchestration using Apache Airflow.
• Develop cloud-native data solutions utilizing AWS services such as S3, Glue, Lambda, and ECS/EKS. Ensure data quality, reliability, security, and governance across the data platform.
• Support AI and analytics initiatives by preparing datasets and building pipelines for ML and Generative AI use cases.
• Collaborate closely with architects, analysts, data scientists, and business stakeholders to deliver scalable data solutions.

Software Engineering, Artificial Intelligence (AI), Amazon Web Services (AWS), Snowflake Schema, Python Programming/Scripting Language, Software Engineering, Artificial Intelligence (AI), Python Programming/Scripting Language, Snowflake Schema, Amazon Web Services (AWS), * Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.

• 5+ years of experience in Data Engineering or Data Platform development.
• Strong hands-on expertise in: Snowflake SQL (Advanced) Python (Advanced) AWS Oracle Apache Airflow Experience designing and supporting enterprise-scale data pipelines and data warehouses.
• Strong understanding of data modeling, performance optimization, and cloud-based data architectures.
• Excellent analytical, problem-solving, and communication skills., * Experience with Snowpark, Streams, Tasks, and Dynamic Tables.
• Exposure to AI/ML, Generative AI, RAG architectures, or vector databases.
• Experience with Spark, Kafka, or Databricks. SnowPro and/or AWS certifications.
• Experience in financial services or capital markets environments.

Ideal Candidate: A hands-on engineer with deep SQL and Python expertise, capable of building scalable cloud-native data solutions while helping enable the organization’s AI and analytics strategy.