Data Engineer
2 months ago
1. Design and Develop ETL Pipelines :
- Extract, transform, and load data from various sources into the data warehouse.
- Ensure data integrity and quality throughout the ETL process.
2. Data Warehousing :
- Design and maintain data models, schemas, and database structures.
- Optimize data storage and retrieval for performance and scalability.
3. Complex SQL Development :
- Write and optimize complex SQL queries for data extraction, reporting, and analysis.
- Utilize advanced SQL techniques, including joins, subqueries, and window functions.
4. Collaboration and Communication :
- Work closely with data analysts, data scientists, and other stakeholders to understand data requirements.
- Communicate findings and data insights effectively to both technical and non-technical audiences.
5. Performance Tuning :
- Monitor and optimize ETL processes and SQL queries for efficiency and speed.
- Troubleshoot and resolve data-related issues as they arise.
6. Documentation and Best Practices :
- Document ETL processes, data models, and data sources for team reference.
- Stay updated with industry trends and best practices in data engineering.
Qualifications :
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- Proven experience as a Data Engineer or in a similar role.
- Strong proficiency in SQL and experience with complex queries.
- Hands-on experience with ETL tools (e.g., Apache NiFi, Talend, Informatica) and data warehousing solutions (e.g., Amazon Redshift, Google BigQuery, Snowflake).
- Familiarity with data modeling concepts and best practices.
- Knowledge of programming languages such as Python or Java is a plus.
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
Preferred Qualifications :
- Experience with cloud platforms (AWS, GCP, Azure).
- Familiarity with big data technologies (Hadoop, Spark).
- Understanding of data governance and compliance requirements.
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