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Job Description

Job Description :


We are seeking a highly skilled Senior Data Engineer with deep experience in Snowflake and modern cloud-based data platforms. The ideal candidate will design, build, optimize, and maintain scalable data pipelines and data warehouse solutions while collaborating closely with analytics, platform, and application teams.


Key Responsibilities :


- Design, develop, and maintain scalable data pipelines using Snowflake


- Architect and optimize data warehouse and data lake solutions


- Lead and support data migration initiatives from on-prem or legacy systems to cloud platforms


- Build and manage ETL/ELT pipelines using Python and cloud-native services


- Implement event-driven data processing using AWS services


- Ensure data quality, reliability, performance tuning, and cost optimization


- Manage and support Kafka clusters, including topic design, partitioning, replication, and monitoring


- Work with MongoDB and other NoSQL databases for data ingestion and integration


- Deploy and manage data workloads in Kubernetes environments


- Collaborate with DevOps and Security teams to implement DevSecOps best practices


- Implement CI/CD pipelines for data engineering workloads


- Monitor, troubleshoot, and resolve production issues


- Mentor junior engineers and contribute to technical design discussions


Required Technical Skills :


Data & Warehousing :


- Strong expertise in Snowflake (architecture, performance tuning, clustering, micro-partitions, streams & tasks)


- Solid understanding of data warehousing concepts (star/snowflake schemas, slowly changing dimensions, fact/dimension tables)


- Experience with data migration and modernization projects


Cloud & Programming :


- Strong experience with AWS, including :


a. S3


b. Lambda


- Event-driven services (EventBridge, SNS/SQS, or similar)


- Proficient in Python for data processing, automation, and pipeline development


Streaming & Messaging :


- Hands-on experience managing Apache Kafka


- Kafka cluster administration, monitoring, scaling, and troubleshooting


- Experience with real-time or near real-time data pipelines

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