ETL Developer

Job Overview/Purpose: The ETL Developer is responsible for creating robust processes that efficiently move data while applying business rules. Collaborating closely with product owners architects developers and business analysts they contribute to innovative data solutions. The role involves designing and implementing data movement processes within a standardized framework to enhance the reliability value and functionality of data assets. Additionally the ETL Developer manages operational support for ETL jobs in production.

Core Competencies:

• Extensive experience with Azure Cloud Platform
• Proficiency in producing highquality technical documentation
• Demonstrated ability to thrive in an Agile development environment and manage time effectively
• Commitment to collaborative teamwork and adaptability within small teams
• Strong verbal and written communication skills for internal interactions and management
• Advanced analytical and problemsolving abilities to address complex issues
• Experience with financial services industry data models
• Eagerness to learn new technologies
• Professionalism attention to detail and ability to perform under pressure
• Demonstrated integrity and selfmotivation
• Effective team player with initiativetaking abilities

Job Skills and Knowledge: Essential:

• Over 7 years of ETL development expertise
• Proficiency in Azure Cloud particularly ADF for pipeline design deployment maintenance and optimization
• Ability to create and maintain technical documentation related to ADF Pipelines and ETL development
• Familiarity with scripting languages (Unix Python PowerShell)
• Experience with job scheduling tools (preferably Airflow)
• Knowledge of Informatica PowerCenter and Developer Client for code interpretation/troubleshooting
• Proficiency in monitoring and troubleshooting production jobs
• Expertise in writing and optimizing SQL queries
• Familiarity with dimensional databases and 3NF data models both logical and physical
• Experience with performance tuning techniques such as partitioning and query plan analysis