Coda Search│Staffing
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer specializing in Spark/Scala to enhance a financial data warehouse in NYC. Contract length is unspecified, with a pay rate of "unknown." Requires 4+ years in Scala/Spark, Kafka knowledge, and financial services experience preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 9, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
New York City Metropolitan Area
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🧠 - Skills detailed
#C++ #Programming #Java #AWS (Amazon Web Services) #Automated Testing #Apache Spark #Datasets #Data Architecture #AWS EMR (Amazon Elastic MapReduce) #Scala #Snowflake #EDW (Enterprise Data Warehouse) #"ETL (Extract #Transform #Load)" #Spark (Apache Spark) #C# #Data Engineering #Kafka (Apache Kafka) #Data Warehouse #Angular #Data Pipeline #Cloud
Role description
Spark / Scala Data Engineer - Streaming Technology Consultant
Location: Onsite - NYC
Contract Opportunity
We are partnering with a leading organization to hire a Spark / Scala Data Engineer to support and enhance a large-scale enterprise data warehouse platform that serves as the single source of truth for financial data across the business.
This role focuses primarily on Spark and Scala development, working within a modern, highly scalable data ecosystem built on technologies such as Spark, Kafka, AWS, and Snowflake. The engineer will contribute to building and optimizing high-volume data pipelines and supporting a streaming data platform used across the enterprise.
The right candidate will bring strong technical expertise while also contributing ideas that improve platform design and overall data architecture.
Principal Responsibilities
• Design, develop, and maintain Spark ETL data pipelines using Scala and Kafka
• Integrate new data feeds and optimize existing data pipelines
• Perform application profiling and performance tuning
• Provide second-line support for data services and related platform components
• Collaborate with cross-functional teams to deliver solutions that handle large volumes of data
• Ensure data is ingested, curated, standardized, stored, and managed appropriately across the platform
• Take end-to-end ownership of development tasks and deliverables
Required Qualifications
• 4+ years of hands-on Scala and Apache Spark development experience (including Spark Streaming)
• Experience with automated testing, including unit, integration, and performance testing
• Background in an object-oriented programming language such as Java, C++, or C#
• 2+ years of professional database development experience across multiple technologies
• Basic knowledge of Kafka and event-driven data pipelines
• Strong analytical and problem-solving skills with the ability to work independently in a fast-paced environment
• Strong communication skills and ability to collaborate with global development teams
Preferred Experience
• Financial services industry experience
• Familiarity with datasets such as Trades, Positions, P&L, Risk Sensitivities, or Reference Data
Technology Exposure
This role offers exposure to a modern technology stack including:
• AWS (EMR, EKS, and other cloud services)
• Snowflake
• Kafka
• Spark / Scala
• Angular and Java for platform enhancements
Spark / Scala Data Engineer - Streaming Technology Consultant
Location: Onsite - NYC
Contract Opportunity
We are partnering with a leading organization to hire a Spark / Scala Data Engineer to support and enhance a large-scale enterprise data warehouse platform that serves as the single source of truth for financial data across the business.
This role focuses primarily on Spark and Scala development, working within a modern, highly scalable data ecosystem built on technologies such as Spark, Kafka, AWS, and Snowflake. The engineer will contribute to building and optimizing high-volume data pipelines and supporting a streaming data platform used across the enterprise.
The right candidate will bring strong technical expertise while also contributing ideas that improve platform design and overall data architecture.
Principal Responsibilities
• Design, develop, and maintain Spark ETL data pipelines using Scala and Kafka
• Integrate new data feeds and optimize existing data pipelines
• Perform application profiling and performance tuning
• Provide second-line support for data services and related platform components
• Collaborate with cross-functional teams to deliver solutions that handle large volumes of data
• Ensure data is ingested, curated, standardized, stored, and managed appropriately across the platform
• Take end-to-end ownership of development tasks and deliverables
Required Qualifications
• 4+ years of hands-on Scala and Apache Spark development experience (including Spark Streaming)
• Experience with automated testing, including unit, integration, and performance testing
• Background in an object-oriented programming language such as Java, C++, or C#
• 2+ years of professional database development experience across multiple technologies
• Basic knowledge of Kafka and event-driven data pipelines
• Strong analytical and problem-solving skills with the ability to work independently in a fast-paced environment
• Strong communication skills and ability to collaborate with global development teams
Preferred Experience
• Financial services industry experience
• Familiarity with datasets such as Trades, Positions, P&L, Risk Sensitivities, or Reference Data
Technology Exposure
This role offers exposure to a modern technology stack including:
• AWS (EMR, EKS, and other cloud services)
• Snowflake
• Kafka
• Spark / Scala
• Angular and Java for platform enhancements
