DataEngineer

Job Title: Data Engineer

Location: Jersey City, NJ (Hybrid)

Duration: 6 Months Contract

Experience: 5+ years

Interview process:

L1 Video interview with Sonata panel

L2 2-3 round of in-person interview with client in 1 day

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.