Description

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.

Required Qualifications

· 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:

o Snowflake

o SQL (Advanced)

o Python (Advanced)

o AWS

o Oracle

o 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

Key Skills

Education

Bachelor's degree