Data Engineer

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. Responsibilities

• 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.

• 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.

Preferred Qualifications

• 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.