Associate, Data Engineer

Job Detail

Experience Level Mid Level
Degree Type Bachelor of Arts (BA)
Employment Full Time
Working Type Hybrid
Job Reference 0000016509
Salary Type Annually
Industry Financial Services
Selling Points
Lead transformative data engineering projects in a hybrid work environment. Optimize Snowflake infrastructure for analytics and AI applications. Access professional growth opportunities and cutting-edge technology resources.

Overview

Shape the future of data engineering by designing scalable solutions for analytics and AI.
Collaborate in a hybrid work environment fostering innovation and professional growth.
Develop and optimize data models and pipelines to drive operational efficiency.
Contribute to data governance practices ensuring quality and compliance standards.
Utilize advanced technologies for processing structured and unstructured data.
Engage with cross-functional teams to implement innovative data solutions.
Enhance system performance through strategic optimizations and cost-effective techniques.
Participate in a dynamic environment supporting analytics and AI initiatives.

Key Responsibilities & Duties

Develop workflows for efficient data ingestion, transformation, and consolidation within Snowflake.
Implement robust frameworks for data governance, access controls, and lineage tracking.
Monitor and resolve data quality issues ensuring reliability and accuracy.
Collaborate with stakeholders to translate business needs into technical solutions.
Optimize Snowflake performance for efficient query execution and cost management.
Design pipelines for processing unstructured data supporting analytics initiatives.
Stay updated on emerging AI tools and technologies to drive innovation.
Contribute to strategic projects enhancing data infrastructure and analytics capabilities.

Job Requirements

Bachelor’s degree in a relevant field with 6+ years of data engineering experience.
Proficiency in Snowflake, SQL, and Python for data processing and pipeline development.
Experience with cloud-based workflows and orchestration systems.
Strong understanding of data governance frameworks and quality standards.
Familiarity with artificial intelligence tools and technologies is advantageous.
Ability to thrive in a hybrid work environment balancing onsite and remote collaboration.
Commitment to continuous learning and professional development supported by the organization.
Excellent problem-solving skills and ability to manage complex data projects.