Data Engineer

Key Responsibilities

• Pipeline Development: Design and build data pipelines to integrate new data sources, with a heavy focus on API-based ingestion.
• Unstructured Data Management: Develop and implement strategies to process, store, and utilize unstructured data formats.
• Snowflake Operations: Handle ongoing Snowflake maintenance tickets, performance tuning, and regular housekeeping of the data warehouse.
• Collaboration: Work closely with Data Quality Analysts and stakeholders to ensure data integrity and flow from scraped document outputs.
• Explore ways to enhance data quality and reliability
• Identify and realize opportunities to acquire better data (raw data)
• Execute data migration from existing databases to the inhouse data warehouse

Qualifications & Skills

• Experience: 5+ years of hands-on experience with Snowflake.
• Technical Proficiency
• Strong proficiency in Python for data processing, scripting, and automation.
• Strong SQL: Advanced proficiency in writing complex, high-performance SQL queries for data transformation and analysis.
• Advanced Snowflake Expertise: Deep experience in Snowflake architecture, including Snowpipe , Streams & Tasks , Zero-Copy Cloning , and Time Travel .
• Extensive hands-on experience with the Snowflake Data Cloud platform.
• API Expertise: Proven ability to build and complete integrations with third-party APIs with Snowflake.

• Cloud Knowledge: Exposure of using Snowflake on Azure and knowledge of Azure Cloud.
• Snowflake SnowPro Certification is a plus.
• Strong understanding or practical experience of at least one common Enterprise Agile Framework e.g.
• Kanban, SAFe, SCRUM, etc.
• Strong understanding of ETL, data warehouse and BI and Advanced Data Analytics concepts
• Strong critical-thinking, analytical and problem-solving skills
• Excellent communicator with team-oriented approach