Data Engineer - Snowflake, Python, AWS & AI

Cardinal Integrated Technologies Inc
  • Jersey City, NJ
  • Quick Apply
2 days ago

Job Description

Role: Data Engineer - Snowflake, Python, AWS & AI(23474-1)
Duration: 6-12+ Months Contract
Location: Jersey City, NJ (4 Days onsite)

Additional Info regarding SO/R:Candidates have to come for in person interview .Client will not compromise on Tech skills. Vet candidates thoroughly before presenting to customer.

Mandatory Areas
  • Data engineering
  • Snow Flake
  • 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.

Numbers & Facts

LocationJersey City, NJ

Skills

  • AWS Lambdaunmatched
  • Amazon Simple Storage Service (S3)unmatched
  • Amazon Web Services (AWS)unmatched
  • Analysis Skillsunmatched
  • Apacheunmatched
  • Application Programming Interface (API)unmatched
  • Architectural Analysisunmatched
  • Artificial Intelligence (AI)unmatched
  • Automationunmatched
  • Capital Marketsunmatched
  • Cloud Computingunmatched
  • Communication Skillsunmatched
  • Computer Scienceunmatched
  • Data Managementunmatched
  • Data Modelingunmatched
  • Data Qualityunmatched
  • Data Scienceunmatched
  • Data Warehousingunmatched
  • Database Extract Transform and Load (ETL)unmatched
  • Financial Servicesunmatched
  • Information Technology & Information Systemsunmatched
  • Multiplatform/Cross-Platformunmatched
  • Oracleunmatched
  • Performance Modelingunmatched
  • Performance Tuning/Optimizationunmatched
  • Problem Solving Skillsunmatched
  • Property Maintenanceunmatched
  • Python Programming/Scripting Languageunmatched
  • SQL (Structured Query Language)unmatched
  • Scalable System Developmentunmatched
  • Snowflake Schemaunmatched
  • Software Engineeringunmatched
  • Training Data Setsunmatched
  • Use Casesunmatched

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