
Data Engineer
4 weeks ago
Key Responsibilities
- Design and develop scalable Data Pipelines to support batch and real-time processing
- Implement efficient Extract, Transform, Load (ETL) processes using tools like Apache Spark and dbt
- Develop and optimize queries using SQL for data analysis and warehousing
- Build and maintain Data Warehousing solutions using platforms like Snowflake or BigQuery
- Collaborate with business and technical teams to gather requirements and create accurate Data Models
- Write reusable and maintainable code in Python (Programming Language) for data ingestion, processing, and automation
- Ensure end-to-end Data Processing integrity, scalability, and performance
- Follow best practices for data governance, security, and compliance
Required Skills & Experience
- 3–4 years of experience in Data Engineering or a similar role
- Strong proficiency in SQL and Python (Programming Language)
- Experience with Extract, Transform, Load (ETL) frameworks and building data pipelines
- Solid understanding of Data Warehousing concepts and architecture
- Hands-on experience with Snowflake, Apache Spark, or similar big data technologies
- Proven experience in Data Modeling and data schema design
- Exposure to Data Processing frameworks and performance optimization techniques
- Familiarity with cloud platforms like AWS, GCP, or Azure
Nice to Have
- Experience with streaming data pipelines (e.g., Kafka, Kinesis)
- Exposure to CI/CD practices in data development
- Prior work in consulting or multi-client environments
- Understanding of data quality frameworks and monitoring strategies
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