ETL Developer

Key Responsibilities

1. ETL Process Design and Development:

• Design, develop, and implement ETL processes for data extraction, transformation, and loading from various data sources into data warehouses and data marts.
• Create and maintain ETL workflows and scripts to ensure efficient and accurate data movement.

2. Data Integration:

• Integrate data from multiple disparate sources, ensuring consistency, accuracy, and completeness.
• Develop and maintain data integration solutions to support business intelligence and analytics requirements.

3. Data Quality and Performance:

• Implement data quality checks and validation routines to ensure the integrity of the data.
• Optimize ETL processes for performance, scalability, and efficiency.

4. Documentation and Maintenance:

• Document ETL processes, data flows, and data models for future reference and maintenance.
• Monitor ETL jobs and workflows to ensure timely and accurate data processing.

5. Collaboration:

• Work closely with data analysts, data scientists, and business stakeholders to understand data requirements and deliver solutions that meet their needs.
• Collaborate with IT and database administrators to ensure data infrastructure supports ETL processes.

6. Troubleshooting and Support:

• Diagnose and resolve issues related to ETL processes and data integration.
• Provide ongoing support and maintenance for ETL processes, ensuring minimal downtime and disruption.

Qualifications

1. Education and Experience:

• Bachelor s degree in computer science, Information Systems, or a related field.
• 1-3 years of proven experience as an ETL Developer or in a similar role.

2. Technical Skills:

• Proficiency in ETL tools such as Oracle Data Integrator (ODI), SQL Server Integration Services (SSIS), and Snowpark.
• Strong SQL skills and experience with database technologies (e.g., Oracle, SQL Server, MySQL).
• Knowledge of data warehousing concepts and data modeling techniques.
• Experience with Databricks and Snowflake.
• Experience with scripting languages (e.g., Python, Shell scripting) is a plus.

3. Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Attention to detail and a commitment to data quality.

4. Additional Skills:

• Experience with cloud data platforms (e.g., AWS, Azure, Google Cloud) is an advantage.
• Familiarity with big data technologies (e.g. Spark) is a plus.