Nasscomm
Azure Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Azure Data Engineer, remote for 2+ months, with a pay rate of "unknown." Key skills include Snowflake, SQL, Azure Data Factory, Kafka, and API integrations. Financial services industry experience is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
August 11, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
New York, United States
-
🧠 - Skills detailed
#Azure ADLS (Azure Data Lake Storage) #Deployment #Data Quality #Storage #Azure Data Factory #Data Integration #ADF (Azure Data Factory) #Data Lake #UAT (User Acceptance Testing) #Snowflake #Azure #Kafka (Apache Kafka) #API (Application Programming Interface) #Automation #Data Governance #SQL (Structured Query Language) #ADLS (Azure Data Lake Storage) #Data Engineering #Data Pipeline #"ETL (Extract #Transform #Load)"
Role description
Position: Azure Data Engineer
Location: Remote
Duration: 2+ Months
Client: Ahead
Job Details:
Seeking Data Engineers to support client Data Program. The resources will provide hands-on support to build and enhance pipelines, implement Snowflake data products, support API and Kafka-based integration work, and move backlog items through development, UAT, and production.
Responsibilities include building and maintaining source-to-target pipelines, developing Snowflake objects and transformation logic, supporting API integrations, implementing Kafka and CDC processing, applying data quality and governance controls, and supporting testing, validation, deployment, and production readiness activities.
The ideal candidate will have experience with Snowflake, SQL, Azure Data Factory, Azure Data Lake Storage, APIs, Kafka, and modern data pipeline delivery. Candidates should be comfortable working across the full lifecycle from design and implementation through testing, deployment, and production support.
Skills Must Have:
• Snowflake
• SQL
• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS)
• API Integrations
• Kafka
• Data Pipeline Development
• ETL / ELT Development
• Data Quality Testing & Validation
• Stored Procedures
• PII Data Handling
• Production Deployment Support
• Data Masking & Tagging
Skills Nice to Have:
• Azure Functions
• Azure API Management (APIM)
• CDC / Delta Processing
• Data Governance
• Data Masking & Tagging
• Near Real-Time Data Integration
• QA / Test Automation
• Production Support
• Enterprise Data Platform Experience
• Financial Services Industry Experience
Position: Azure Data Engineer
Location: Remote
Duration: 2+ Months
Client: Ahead
Job Details:
Seeking Data Engineers to support client Data Program. The resources will provide hands-on support to build and enhance pipelines, implement Snowflake data products, support API and Kafka-based integration work, and move backlog items through development, UAT, and production.
Responsibilities include building and maintaining source-to-target pipelines, developing Snowflake objects and transformation logic, supporting API integrations, implementing Kafka and CDC processing, applying data quality and governance controls, and supporting testing, validation, deployment, and production readiness activities.
The ideal candidate will have experience with Snowflake, SQL, Azure Data Factory, Azure Data Lake Storage, APIs, Kafka, and modern data pipeline delivery. Candidates should be comfortable working across the full lifecycle from design and implementation through testing, deployment, and production support.
Skills Must Have:
• Snowflake
• SQL
• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS)
• API Integrations
• Kafka
• Data Pipeline Development
• ETL / ELT Development
• Data Quality Testing & Validation
• Stored Procedures
• PII Data Handling
• Production Deployment Support
• Data Masking & Tagging
Skills Nice to Have:
• Azure Functions
• Azure API Management (APIM)
• CDC / Delta Processing
• Data Governance
• Data Masking & Tagging
• Near Real-Time Data Integration
• QA / Test Automation
• Production Support
• Enterprise Data Platform Experience
• Financial Services Industry Experience
