Snowflake Data Engineer

Job Description:

Analyze internal and external raw data to generate BI and Advanced Analytics datasets based on stakeholder requirements.
Design and develop data pipelines to curate sourced data into the in-house data warehouse.
Create data marts to facilitate dataset consumption by business and IT stakeholders.
Propose and implement data model changes that align with in-house data warehouse standards.
Plan and execute data migration from existing database solutions to the in-house data warehouse.
Perform regular housekeeping of raw and stored data to ensure data quality and efficiency.
Build, maintain, and optimize data pipelines and data platforms.
Develop prototypes for data solutions and analytical tooling to support BI and advanced analytics activities.
Explore and implement methods to improve data quality, reliability, and acquisition processes.
Promote and enforce data engineering standards and best practices across the organization.

Required Skills & Qualifications:

Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related quantitative discipline from a top-tier university.
AWS Certified Data Engineer – Specialty or AWS Solutions Architect – Associate.
Snowflake SnowPro Core Certification.
7+ years of experience in data engineering or a similar role, preferably in the financial industry.
Strong knowledge of at least one Enterprise Agile Framework (e.g., Kanban, SAFe, SCRUM).
Solid understanding of ETL, data warehousing, BI (Qlik), and advanced data analytics concepts.
Expertise in cloud technologies such as AWS RDS and AWS Fargate.
Hands-on experience with databases and data warehouses (Snowflake, PostgreSQL, MS SQL).
Strong programming skills in Java and/or Python.
Practical experience with ETL tools such as AWS Glue.
Excellent problem-solving, analytical, and critical-thinking skills.
Strong communication skills with a collaborative, team-oriented approach.

Snowflake Data Engineer

11 Aug Snowflake Data Engineer