AWS DATA ENGINEER

Title: AWS Data Engineer – Snowflake, Python, AWS & AI

Work Location: Jersey City, NJ (3 days onsite) - In-person interview will happen

Duration: Long Term Contract

Job Description

Position Summary

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.

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

Snowflake SQL Python AWS Oracle Airflow ETL/ELT Data Warehousing Data Modeling Snowpark AI/GenAI Data Governance

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.