
Data Engineer
4 weeks ago
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Qualifications:- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
- 3 to 4 years of experience as a Data Engineer in a production environment.
- Hands-on experience with AWS Redshift, AWS Data Lake, Snowflake, and strong SQL skills.
- Experience with data pipelines using AWS Glue, PySpark, or Airflow.
- Knowledge of data warehousing, dimensional modeling, and performance tuning.
- Proficiency in Python or Scala for data transformation.
- Understanding of data privacy, security, and compliance standards (a plus).
- Experience with data cataloging tools like AWS Glue Data Catalog or Apache Hive Metastore.
- Exposure to streaming frameworks like Kinesis, Kafka, or Spark Streaming.
- Experience with BI tools such as Power BI, Looker, Tableau integrated with Redshift or Snowflake.
- Familiarity with Terraform or Infrastructure as Code tools (a bonus).
- Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion into AWS Redshift, Data Lake, and Snowflake.
- Create data models and schemas optimized for analytics and reporting.
- Collaborate with analysts, product teams, and engineers to meet data requirements.
- Manage scheduled jobs to ensure data quality and reliability.
- Implement data governance, cataloging, and security standards.
- Optimize SQL queries and ETL processes for performance and cost-efficiency.
- Utilize AWS services like Glue, Lambda, S3, Athena, Redshift Spectrum, etc., for pipeline operations.
- Perform data validation and quality checks.
- Troubleshoot data issues across pipelines and cloud environments.
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