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ETL Developer
1 month ago
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.
2-4 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.