Snowflake Data Engineer
5 days ago
Job Description :
Key Responsibilities :
- Lead the architecture and implementation of application data stores using PostgreSQL, DynamoDB, and advanced SQL to support diverse application needs.
- Develop efficient data processing workflows using SQL, Python, and PySpark across structured (CSV, SQL), semi-structured (JSON, XML), and unstructured (PDF, logs) data formats.
- Utilize deep knowledge of Azure and AWS data ecosystems, including Microsoft Fabric and distributed computing frameworks, to design robust data solutions.
- Architect low-latency, high-throughput data pipelines using Apache Spark and cloud-native services ensuring high availability and fault tolerance.
- Implement CI/CD pipelines, automation scripts, schema versioning, and enforce rigorous data security and governance policies in production environments.
- Ensure best practices around data performance, scalability, compliance, and cost optimization are strictly followed.
- Collaborate with data scientists, analysts, and cross-functional teams to deliver reliable and scalable data solutions.
- Continuously evaluate and recommend improvements in data architecture and processes to support evolving business needs.
Required Skills & Qualifications :
- Strong programming skills in SQL, Python, and PySpark for complex data transformations and pipeline development.
- Extensive experience working with various data formats : structured, semi-structured, and unstructured.
- In-depth knowledge of PostgreSQL and DynamoDB for designing and managing application data stores.
- Strong understanding of cloud data ecosystems in Azure and AWS, including Microsoft Fabric and distributed computing frameworks.
- Experience designing and maintaining scalable batch and streaming pipelines with a focus on low latency and high throughput.
- Familiarity with CI/CD automation, schema versioning, and production-grade data security practices.
- Ability to apply best practices in data engineering including performance tuning, data governance, and compliance standards.
- Excellent problem-solving skills and ability to work collaboratively in a team environment.
Preferred Qualifications :
- Prior exposure to data mesh architectures or data lakehouse concepts.
- Certifications in Snowflake, Databricks, Azure, or AWS data engineering.
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