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Job Description & How to Apply Below
Senior Snowflake Data Engineer
Location:
Remote
Experience :7+ Years
Job Type: Full-Time
About the Role:
We are seeking a highly skilled Senior Snowflake Data Engineer with strong experience in Python, PySpark, Snowflake , and AWS Glue to join our growing data team. You will be responsible for building scalable and reliable data pipelines that drive business insights and operational efficiency. This role requires a deep understanding of data modelling, ETL frameworks, and cloud-based data platforms.
Key Responsibilities:
Design, develop, and maintain scalable ETL/ELT pipelines using PySpark and AWS Glue .
Build and optimize data models in Snowflake to support reporting, analytics, and machine learning workloads.
Automate data ingestion from various sources including APIs, databases, and third-party platforms.
Ensure high data quality and implement data validation and monitoring processes.
Collaborate with data analysts, data scientists, and other engineers to understand data requirements and deliver high-quality solutions.
Work with large datasets in structured and semi-structured formats (JSON, Parquet, Avro, etc.).
Participate in code reviews, performance tuning, and debugging of data workflows.
Implement security and compliance measures across data pipelines and storage.
Required Skills &
Qualifications:
7+ years of experience as a Data Engineer or similar role.
Proficiency in Python for data manipulation and scripting.
Hands-on experience with PySpark for large-scale data processing.
5+ years expertise in Snowflake – data modeling, performance tuning, and SnowSQL.
Solid experience with AWS Glue , including Glue Jobs, Crawlers, and Data Catalog integration.
Experience with other AWS services like S3, Lambda, Athena, Cloud Watch , etc.
Familiarity with CI/CD pipelines and version control tools (e.g., Git).
Understanding of data warehousing concepts, dimensional modeling, and ETL best practices.
Excellent problem-solving skills and attention to detail.
Preferred Qualifications:
AWS Certification (e.g., AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect).
Experience with orchestration tools such as Apache Airflow or AWS Step Functions .
Exposure to Dev Ops practices and infrastructure-as-code (e.g., Terraform or Cloud Formation).
Experience working in Agile/Scrum environments.
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