Geode Capital Management is seeking a highly motivated Associate Data Engineer to join our Data team. The engineer will report to the Director of Data Engineering. This role will focus on designing and building scalable data solutions, working closely with various operations teams, data analysts, architects, and business stakeholders. The Data Engineer will help Geode modernize cloud native data and analytics platform centered around technologies such as AWS, Snowflake, DBT, Snaplogic, and Python.
This role is based out of our office in Boston, Massachusetts and is required to follow the firm’s current hybrid work schedule: Tuesday, Wednesday and Thursday in-office, with the option to work Monday and Friday remote from home.

Responsibilities:

• Build Modern Data pipelines to ingest, process and store enterprise data
• Contribute to the design, development, and implementation of innovative data pipelines and solutions using AWS, Snowflake, Snaplogic, Python
• Continuously enhance data pipelines through automation, efficient unit testing and increasing test coverage and quality
• Collaborate with the Data product lead, Scrum Masters, architects and development teams to build effective data ingestion and integration pipelines.

SKILLS YOU BRING:

• A bachelor’s degree in computer science or a similar field
• 3-5 years of data and software engineering experience with a focus on development, implementation, and maintenance of data pipelines
• Strong skills in ETL/ELT development using Python and Snowflake
• Strong skills in data modeling, database design, and SQL development
• Effective communication and interpersonal skills
• Experience with DBT or Snaplogic is a plus
• Experience with scheduling tools such as Control-M or Autosys is a plus
• Experience working in the Asset management industry is a plus

• Build Modern Data pipelines to ingest, process and store enterprise data
• Contribute to the design, development, and implementation of innovative data pipelines and solutions using AWS, Snowflake, Snaplogic, Python
• Continuously enhance data pipelines through automation, efficient unit testing and increasing test coverage and quality
• Collaborate with the Data product lead, Scrum Masters, architects and development teams to build effective data ingestion and integration pipelines