Synergyassure Inc
AWS DATA ENGINEER
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer with a long-term contract in Jersey City, NJ, offering a pay rate of "unknown." Requires 5+ years of experience in Snowflake, Python, SQL, AWS, and data pipeline development.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
August 5, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
New Jersey, United States
-
🧠 - Skills detailed
#Snowflake #Oracle #Databricks #Spark (Apache Spark) #Strategy #SQL (Structured Query Language) #Snowpark #Data Governance #Data Architecture #Airflow #Data Science #Datasets #Computer Science #Data Warehouse #AI (Artificial Intelligence) #Lambda (AWS Lambda) #ML (Machine Learning) #Data Engineering #Cloud #Data Modeling #Automation #Apache Airflow #AWS (Amazon Web Services) #Security #Scala #Data Quality #Data Pipeline #Databases #Python #S3 (Amazon Simple Storage Service) #Kafka (Apache Kafka) #"ETL (Extract #Transform #Load)"
Role description
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.
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.
