Role: Data Engineer - Snowflake, Python, AWS & AI Duration: 6-12+ Months Contract Location: Jersey City, NJ (4 Days onsite) (Only local candidates will work out)
Additional Info regarding SO/R: Candidates must attend an in-person interview.
Mandatory Areas
- Data engineering
- Snowflake
- Python, AWS
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: 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.
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.
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