Data Engineer

At GoodUnited, we use conversational messaging technology and human insight to help nonprofits acquire and activate supporters, build meaningful relationships at scale, and grow revenue in social channels.

At GoodUnited, we use conversational messaging technology and human insight to help nonprofits acquire and activate supporters, build meaningful relationships at scale, and grow revenue in social channels.

The Data Engineer will be responsible for expanding and optimizing our data and data pipeline architecture. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.

The Data Engineer will support our software engineers, database architects and data scientists on data initiatives and will ensure a consistent, optimal architecture. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of building and optimizing our data architecture to support our next generation of products and data initiatives.

What does a Data Engineer do at GoodUnited?:

• Maintains an optimal data pipeline architecture.
• Assembles complex data sets that meet functional / non-functional business requirements.
• Identifies, designs, and implements internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Builds the infrastructure required for extraction, transformation, and loading of data from a wide variety of data sources .

What experience and skills does a Senior Data Engineer need to be successful here?:

• 2+ years of experience in a Data Engineer role, with a degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
• Experience building and optimizing data pipelines, architectures and data sets.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of relational SQL and NoSQL databases, including Postgres and MongoDB.
• Experience with ETL tools, preferably Matillion.
• Experience with data lakes/warehouses, preferably Snowflake.
• Experience with AWS cloud services: EC2, RDS, Redshift, Glue, Athena
• Experience with scripting languages: Python, NodeJS, etc.