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Key Responsibilities and Required Skills for Azure Data Factory Developer

💰 $80,000 - $140,000

Data EngineeringCloud ComputingAzure

🎯 Role Definition

An Azure Data Factory (ADF) Developer is responsible for designing, developing, and maintaining ETL (Extract, Transform, Load) pipelines and data integration solutions using Microsoft Azure Data Factory. This role requires expertise in cloud-based data workflows, SQL, and data modeling. The ADF Developer collaborates with data engineers, analysts, and business stakeholders to ensure reliable, scalable, and high-performance data pipelines that meet organizational analytics and reporting needs.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Data Engineer
  • ETL Developer
  • SQL Developer

Advancement To:

  • Senior Azure Data Engineer
  • Data Architect
  • Cloud Solutions Architect

Lateral Moves:

  • Power BI Developer
  • Azure Synapse Developer

Core Responsibilities

Primary Functions

  1. Design, develop, and maintain ETL pipelines using Azure Data Factory.
  2. Integrate data from multiple sources including on-premises and cloud systems.
  3. Implement data transformations and cleansing using ADF Mapping Data Flows and pipelines.
  4. Monitor, troubleshoot, and optimize pipeline performance and execution.
  5. Collaborate with data engineers and architects to define data models and workflow designs.
  6. Ensure data quality, consistency, and governance throughout ETL processes.
  7. Implement incremental data load strategies and change data capture (CDC) processes.
  8. Develop automation scripts for scheduling and pipeline orchestration.
  9. Conduct unit testing, integration testing, and validation of ETL pipelines.
  10. Maintain documentation for pipeline designs, workflow processes, and technical specifications.
  11. Implement logging, alerting, and error-handling mechanisms for pipelines.
  12. Work closely with DevOps teams for CI/CD integration and automated deployment.
  13. Optimize data pipelines for performance, scalability, and cost efficiency.
  14. Participate in requirement gathering sessions and translate business needs into technical specifications.
  15. Stay current with Azure platform updates, best practices, and cloud data integration tools.
  16. Assist in the migration of legacy ETL processes to Azure Data Factory.
  17. Provide support for production issues and troubleshoot pipeline failures.
  18. Ensure compliance with data privacy, security policies, and regulatory requirements.
  19. Collaborate with business intelligence teams to support analytics and reporting.
  20. Mentor junior developers and provide guidance on best practices for cloud ETL development.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Assist in proof-of-concept and prototyping new data integration solutions.

Required Skills & Competencies

Hard Skills (Technical)

  • Proficient in Azure Data Factory, Mapping Data Flows, and pipeline orchestration
  • Strong SQL and T-SQL programming skills
  • Experience with Azure SQL Database, Azure Synapse, and Data Lake Storage
  • Knowledge of ETL/ELT concepts, best practices, and patterns
  • Familiarity with PowerShell or Python for automation and scripting
  • Understanding of data modeling, normalization, and schema design
  • Experience with incremental loads, change data capture (CDC), and data partitioning
  • Knowledge of cloud security, access controls, and compliance requirements
  • Experience with version control (Git) and CI/CD pipelines in Azure DevOps
  • Familiarity with monitoring, logging, and troubleshooting ADF pipelines

Soft Skills

  • Strong analytical and problem-solving skills
  • Excellent communication and collaboration abilities
  • Ability to manage multiple priorities in a fast-paced environment
  • Detail-oriented with a focus on data quality and accuracy
  • Proactive learning mindset for adopting new cloud technologies
  • Mentorship and knowledge-sharing skills
  • Ability to translate technical concepts for business stakeholders

Education & Experience

Educational Background

Minimum Education:

  • Bachelor’s degree in Computer Science, Information Technology, or a related field

Preferred Education:

  • Master’s degree in Data Science, Cloud Computing, or Software Engineering

Relevant Fields of Study:

  • Computer Science
  • Information Systems
  • Data Engineering
  • Cloud Computing

Experience Requirements

Typical Experience Range: 2-5 years in Azure Data Factory or cloud ETL development

Preferred:

  • Proven experience building scalable and efficient data pipelines in Azure
  • Hands-on experience with cloud-based analytics and reporting solutions
  • Experience mentoring or leading junior developers on ETL projects
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