BCforward
Senior Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer with 5-10 years of experience, focusing on ETL pipelines in a financial data exchange project. Key skills include PySpark, AWS Glue, Snowflake, and Python. Contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 22, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
New York, United States
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🧠 - Skills detailed
#Data Quality #Apache Airflow #Big Data #Python #Airflow #Scala #AWS EMR (Amazon Elastic MapReduce) #Data Processing #Spark (Apache Spark) #Data Ingestion #Security #"ETL (Extract #Transform #Load)" #Data Lake #Snowflake #Apache Spark #AWS (Amazon Web Services) #Data Analysis #Java #Data Engineering #PySpark #Cloud #Programming #AWS Glue #Data Security
Role description
Job Responsibilities:
• Create/manage ETL pipelines for the data lake and Snowflake; automate data analysis/aggregation work.
• Design, build, and manage scalable ETL pipelines for a data lake and Snowflake environment, ensuring efficient data ingestion, transformation, and loading.
• Automate data analysis and aggregation processes to support business insights and reporting.
• Collaborate with cross-functional teams to optimize data workflows and maintain data quality.
Key Skills:
Data lake, AWS, ETL, Snowflake, Control‑M, Apache Airflow, PySpark, Java Spark
Hiring Manager Notes:
Experience: 5–10 years
Project: Large-scale Financial Data Exchange & Data Security platform handling transaction processing and data movement.
Role: 60% Data Engineering, 40% Programming (Python/Java).
Must-Have Skills:
• PySpark (Strong hands-on experience)
• Apache Spark
• AWS Glue ETL
• AWS EMR
• Snowflake
• Python
• Java
• Data Structures & Algorithms
• AWS/Cloud Infrastructure
Preferred Domain: Banking, Financial Services, Payments, Transaction Processing.
Interview Process: Zoom interview with Live Coding; onsite may be required.
Ideal Candidate: Senior Big Data Engineer with strong PySpark, AWS Glue/EMR, Snowflake, and Python skills, capable of building scalable financial data processing solutions.
Job Responsibilities:
• Create/manage ETL pipelines for the data lake and Snowflake; automate data analysis/aggregation work.
• Design, build, and manage scalable ETL pipelines for a data lake and Snowflake environment, ensuring efficient data ingestion, transformation, and loading.
• Automate data analysis and aggregation processes to support business insights and reporting.
• Collaborate with cross-functional teams to optimize data workflows and maintain data quality.
Key Skills:
Data lake, AWS, ETL, Snowflake, Control‑M, Apache Airflow, PySpark, Java Spark
Hiring Manager Notes:
Experience: 5–10 years
Project: Large-scale Financial Data Exchange & Data Security platform handling transaction processing and data movement.
Role: 60% Data Engineering, 40% Programming (Python/Java).
Must-Have Skills:
• PySpark (Strong hands-on experience)
• Apache Spark
• AWS Glue ETL
• AWS EMR
• Snowflake
• Python
• Java
• Data Structures & Algorithms
• AWS/Cloud Infrastructure
Preferred Domain: Banking, Financial Services, Payments, Transaction Processing.
Interview Process: Zoom interview with Live Coding; onsite may be required.
Ideal Candidate: Senior Big Data Engineer with strong PySpark, AWS Glue/EMR, Snowflake, and Python skills, capable of building scalable financial data processing solutions.
