Zeektek
ADF (Azure)Data Engineer - Informatica/ADF/Fabric/Python/SQL
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an ADF (Azure) Data Engineer on a 2-year contract, 100% remote, with a pay rate of "unknown." Key skills include Python, PySpark, SQL, and experience with Microsoft Fabric, Azure Data Factory, and cloud data pipelines.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
592
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🗓️ - Date
August 4, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Version Control #Azure ADLS (Azure Data Lake Storage) #Lambda (AWS Lambda) #Big Data #Databricks #Kappa Architecture #Data Lake #Azure #Data Engineering #Azure Data Factory #PySpark #GIT #"ETL (Extract #Transform #Load)" #Informatica #Data Layers #Computer Science #Cloud #Scala #Azure DevOps #Python #Data Pipeline #ADLS (Azure Data Lake Storage) #Spark (Apache Spark) #Storage #ADF (Azure Data Factory) #DevOps #SQL (Structured Query Language)
Role description
2-year contract - potential to convert after 2 years
100% remote
Summary / Duties:
The Data Engineer will independently design, build, and optimize cloud-based data pipelines supporting analytics and reporting initiatives. Responsibilities include selecting ingestion patterns, engineering high-performance processing jobs, analyzing execution plans, and optimizing compute resources, partition strategies, latency, and cloud costs. The role will implement governable Lakehouse and Medallion data layers using Microsoft Fabric, Databricks, Azure Data Factory, and Azure Data Lake Storage. Additional duties include developing advanced Python and PySpark transformation modules, managing pipelines through code and version control, supporting CI/CD workflows, and diagnosing network, data-distribution, and code-performance issues. The engineer will apply strong SQL skills, establish scalable engineering standards, and mentor junior team members
Requirements:
• Bachelor’s degree in Computer Science, Information Systems, Engineering, a related technical field, or equivalent experience
• 8+ years of experience in data engineering, software engineering, or big data development
• Experience independently architecting and building end-to-end data pipelines in a cloud environment
• Strong proficiency in Python, PySpark, and SQL
• Experience with Microsoft Fabric, Databricks, Azure Data Factory, and Azure Data Lake Storage
• Experience with Lakehouse, Medallion, and Lambda or Kappa architectures
• Experience with CI/CD, Azure DevOps, Git, and orchestration tools
• Ability to optimize distributed data-processing jobs, compute sizing, partitioning, and cloud costs
Preferred Requirements:
• Experience developing infrastructure and data pipelines as code
• Knowledge of Spark internals and distributed-computing concepts
• Experience with Delta and Parquet file formats
• Experience diagnosing systemic pipeline, network, data-skew, and code-performance issues
• Ability to mentor junior and associate data engineers
2-year contract - potential to convert after 2 years
100% remote
Summary / Duties:
The Data Engineer will independently design, build, and optimize cloud-based data pipelines supporting analytics and reporting initiatives. Responsibilities include selecting ingestion patterns, engineering high-performance processing jobs, analyzing execution plans, and optimizing compute resources, partition strategies, latency, and cloud costs. The role will implement governable Lakehouse and Medallion data layers using Microsoft Fabric, Databricks, Azure Data Factory, and Azure Data Lake Storage. Additional duties include developing advanced Python and PySpark transformation modules, managing pipelines through code and version control, supporting CI/CD workflows, and diagnosing network, data-distribution, and code-performance issues. The engineer will apply strong SQL skills, establish scalable engineering standards, and mentor junior team members
Requirements:
• Bachelor’s degree in Computer Science, Information Systems, Engineering, a related technical field, or equivalent experience
• 8+ years of experience in data engineering, software engineering, or big data development
• Experience independently architecting and building end-to-end data pipelines in a cloud environment
• Strong proficiency in Python, PySpark, and SQL
• Experience with Microsoft Fabric, Databricks, Azure Data Factory, and Azure Data Lake Storage
• Experience with Lakehouse, Medallion, and Lambda or Kappa architectures
• Experience with CI/CD, Azure DevOps, Git, and orchestration tools
• Ability to optimize distributed data-processing jobs, compute sizing, partitioning, and cloud costs
Preferred Requirements:
• Experience developing infrastructure and data pipelines as code
• Knowledge of Spark internals and distributed-computing concepts
• Experience with Delta and Parquet file formats
• Experience diagnosing systemic pipeline, network, data-skew, and code-performance issues
• Ability to mentor junior and associate data engineers
