Data Engineer - Snowflake

Key Responsibilities:

• Design & Build: Develop scalable, resilient ETL workflows and real-time data pipelines using Python, PySpark, and AWS services.
• Cloud Engineering: Utilize AWS services such as Glue, Lambda, EC2, RDS, and S3 to build efficient cloud-based data architectures.
• Snowflake Integration: Design and maintain data models, pipelines, and ingestion processes within Snowflake, ensuring performance and scalability.
• API Development: Integrate RESTful and other APIs to ingest and synchronize external and internal datasets.
• Optimization: Monitor and tune the performance of data workflows, pipelines, and queries for minimal latency and high throughput.
• Collaboration: Partner with data analysts, scientists, and stakeholders to define and deliver data requirements.

Required Skills & Qualifications:

• Experience Level: 4+ years in data engineering or related roles.
• Programming Expertise: Proficient in Python and PySpark, with a strong background in data transformation and API integration.
• AWS Mastery: Deep hands-on experience with AWS Glue, Lambda, EC2, RDS, and S3.
• ETL & Real-Time Pipelines: Proven ability to build and scale batch and streaming data workflows.
• Snowflake: Hands-on experience with Snowflake data warehouse, including data modeling, Snowpipe, and performance tuning.
• API Integration: Strong understanding of REST APIs, JSON, and secure authentication protocols.
• Data Systems: Proficiency in relational databases (e.g., PostgreSQL, MySQL) and best practices in data warehousing.
• Problem Solver: Strong analytical skills with a knack for identifying and solving complex data challenges.