Snowflake Data Engineer

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.