Phyton Talent Advisors
Data Engineer (Investment Banking)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (Investment Banking) with a contract length of "unknown" and a pay rate of "unknown." Key skills include Snowflake, Python, SQL, and AWS. Requires 5+ years of experience and a Bachelor's degree in a related field.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
624
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🗓️ - Date
August 4, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
Jersey City, NJ
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🧠 - Skills detailed
#Apache Airflow #Data Science #Data Governance #Databases #Automation #Airflow #Oracle #Microsoft Power BI #Data Engineering #Data Architecture #"ETL (Extract #Transform #Load)" #Snowflake #Snowpark #Data Warehouse #Computer Science #Security #ML (Machine Learning) #Cloud #AWS (Amazon Web Services) #Scala #Kafka (Apache Kafka) #Python #Data Pipeline #Data Modeling #AI (Artificial Intelligence) #Datasets #Data Quality #BI (Business Intelligence) #Qlik #SQL (Structured Query Language) #Strategy
Role 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, Power BI/Qlik, AWS, Oracle, and Apache Airflow, with exposure to AI/Generative AI technologies.
Responsibilitie
1. Design, build, and maintain scalable ETL/ELT data pipelines using Python and SQL
1. Develop and optimize data solutions in Snowflake, including data modeling, performance tuning, and automation
1. Integrate and transform data from Oracle, APIs, flat files, AWS services, and other enterprise systems
1. Build and manage workflow orchestration using TWS/ Apache Airflow
1. Ensure data quality, reliability, security, and governance across the data platform
1. Support AI and analytics initiatives by preparing datasets and building pipelines for ML and Generative AI use cases
1. Collaborate closely with architects, analysts, data scientists, and business stakeholders to deliver scalable data solutions
.
Required Qualificatio
1. Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
1. 5+ years of experience in Data Engineering or Data Platform development.
1. Strong hands-on expertise in Snowflake
1. SQL (Advanced)
1. Python (Advanced)
1. Power BI/Qlik
1. AWS
1. Oracle
1. Apache Airflow
1. Experience designing and supporting enterprise-scale data pipelines and data warehouses
1. Strong understanding of data modeling, performance optimization, and cloud-based data architectures
1. Excellent analytical, problem-solving, and communication skills.
Preferred Qualifications
1. Experience with Snowpark, Streams, Tasks, and Dynamic Tables
1. Exposure to AI/ML, Generative AI, RAG architectures, or vector databases
1. Experience with Kafka
1. SnowPro and/or AWS certification
1. Experience in financial services or capital markets environments.
Key Skills
iSnowflake | SQL | Python | Power BI/Qlik | 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.
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, Power BI/Qlik, AWS, Oracle, and Apache Airflow, with exposure to AI/Generative AI technologies.
Responsibilitie
1. Design, build, and maintain scalable ETL/ELT data pipelines using Python and SQL
1. Develop and optimize data solutions in Snowflake, including data modeling, performance tuning, and automation
1. Integrate and transform data from Oracle, APIs, flat files, AWS services, and other enterprise systems
1. Build and manage workflow orchestration using TWS/ Apache Airflow
1. Ensure data quality, reliability, security, and governance across the data platform
1. Support AI and analytics initiatives by preparing datasets and building pipelines for ML and Generative AI use cases
1. Collaborate closely with architects, analysts, data scientists, and business stakeholders to deliver scalable data solutions
.
Required Qualificatio
1. Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
1. 5+ years of experience in Data Engineering or Data Platform development.
1. Strong hands-on expertise in Snowflake
1. SQL (Advanced)
1. Python (Advanced)
1. Power BI/Qlik
1. AWS
1. Oracle
1. Apache Airflow
1. Experience designing and supporting enterprise-scale data pipelines and data warehouses
1. Strong understanding of data modeling, performance optimization, and cloud-based data architectures
1. Excellent analytical, problem-solving, and communication skills.
Preferred Qualifications
1. Experience with Snowpark, Streams, Tasks, and Dynamic Tables
1. Exposure to AI/ML, Generative AI, RAG architectures, or vector databases
1. Experience with Kafka
1. SnowPro and/or AWS certification
1. Experience in financial services or capital markets environments.
Key Skills
iSnowflake | SQL | Python | Power BI/Qlik | 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.
