Accion Labs
Azure Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Azure Data Engineer on a 3-6 month contract, offering remote work. Key skills include Azure Databricks, Data Factory, and strong SQL development. A degree in Computer Science or related field is required, with data engineering experience preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 30, 2026
🕒 - Duration
3 to 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Synapse #REST (Representational State Transfer) #Databricks #Batch #Data Governance #Azure Data Factory #Monitoring #Data Lake #Snowflake #Scala #Data Layers #"ETL (Extract #Transform #Load)" #Cloud #Data Engineering #SQL (Structured Query Language) #Documentation #Metadata #DevOps #Computer Science #Databases #Delta Lake #JSON (JavaScript Object Notation) #SSIS (SQL Server Integration Services) #BI (Business Intelligence) #PySpark #Deployment #Azure Databricks #Spark (Apache Spark) #GIT #Azure #ADF (Azure Data Factory) #Datasets
Role description
Remote - Hiring for Azure Data Engineer – Azure Databricks & Data Factory - 3-6 months contract
Azure Databricks, , Azure Data Factory (ADF), Azure Synapse and Pyspark
Required Skills & Experience:
Experience in data engineering or ETL development, preferably within a cloud ecosystem.
Azure Databricks (PySpark, SparkSQL, Delta Lake)
Azure Data Factory (ADF) pipelines and orchestration
Azure Synapse / Data Lake / SQL Database
Deep understanding of data warehousing concepts, star/snowflake schemas, and performance tuning.
Experience integrating data from APIs (REST/JSON) and third-party platforms.
Solid SQL development skills with ability to write optimized queries and DDL scripts.
Familiarity with source control (Git), DevOps CI/CD pipelines, and data governance practices.
Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
Key Responsibilities:
Design, develop, and maintain ETL pipelines using Azure Data Factory and Databricks for ingestion, transformation, and integration of large-scale datasets.
Build and optimize Databricks notebooks (PySpark/SparkSQL) for batch and streaming workloads.
Migrate and modernize legacy ETL workflows (e.g., SSIS, stored procedures) into scalable Databricks-based processes.
Integrate data from various sources including APIs, relational databases, and cloud data stores into Azure Data Lake and Synapse.
Implement robust data validation, monitoring, and quality checks across data layers.
Collaborate with analytics, BI, and business teams to design curated data models supporting key business use cases.
Develop and maintain metadata, data dictionaries, and lineage documentation.
Work with DevOps and Cloud teams to automate deployments and schedule data workflows.
Remote - Hiring for Azure Data Engineer – Azure Databricks & Data Factory - 3-6 months contract
Azure Databricks, , Azure Data Factory (ADF), Azure Synapse and Pyspark
Required Skills & Experience:
Experience in data engineering or ETL development, preferably within a cloud ecosystem.
Azure Databricks (PySpark, SparkSQL, Delta Lake)
Azure Data Factory (ADF) pipelines and orchestration
Azure Synapse / Data Lake / SQL Database
Deep understanding of data warehousing concepts, star/snowflake schemas, and performance tuning.
Experience integrating data from APIs (REST/JSON) and third-party platforms.
Solid SQL development skills with ability to write optimized queries and DDL scripts.
Familiarity with source control (Git), DevOps CI/CD pipelines, and data governance practices.
Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
Key Responsibilities:
Design, develop, and maintain ETL pipelines using Azure Data Factory and Databricks for ingestion, transformation, and integration of large-scale datasets.
Build and optimize Databricks notebooks (PySpark/SparkSQL) for batch and streaming workloads.
Migrate and modernize legacy ETL workflows (e.g., SSIS, stored procedures) into scalable Databricks-based processes.
Integrate data from various sources including APIs, relational databases, and cloud data stores into Azure Data Lake and Synapse.
Implement robust data validation, monitoring, and quality checks across data layers.
Collaborate with analytics, BI, and business teams to design curated data models supporting key business use cases.
Develop and maintain metadata, data dictionaries, and lineage documentation.
Work with DevOps and Cloud teams to automate deployments and schedule data workflows.
