Analytics Engineer

Givebutter

1d•Remote

About The Position

Givebutter is seeking a curious and technically strong Analytics Engineer to join our growing Data team. This role partners closely with engineers, analysts, and stakeholders to understand business needs, uncover insights in our data, and build reliable data systems that scale with the company. You’ll help maintain and expand our analytical data model, monitor and improve our data pipelines, and investigate complex data questions across our systems. As part of this work, you’ll also contribute to the documentation and structured context that helps both stakeholders and internal AI tools effectively interact with our data.

Requirements

2+ years of experience working in analytics engineering, data engineering, or analytics roles.
Strong SQL skills and experience working with relational data warehouses.
Hands-on experience working with Snowflake as a cloud data warehouse.
Hands-on experience developing and maintaining models using dbt.
Experience using Python for data workflows, scripting, or API integrations
Understanding of analytical data modeling concepts including fact tables, dimensions, star/snowflake schema, and partitioning.
Ability to independently investigate and resolve complex data issues across multiple systems.
Strong communication skills and the ability to collaborate with both technical and non-technical stakeholders.
Ability to work independently, investigate ambiguous problems, and propose improvements to the data platform.

Nice To Haves

Experience designing and maintaining analytical data models that support reporting and operational decision-making.
Worked with modern data stacks and understand how to build and maintain reliable data pipelines.
Can partner with Product, Engineering, and business stakeholders to understand data needs and translate them into technical solutions.
Enjoy performing deep data investigation and root-cause analysis when numbers don’t look right.
Genuinely excited about working with AI, eager to explore new tools, experiment with use cases, and actively champion its adoption to improve workflows and decision-making across the organization.
Care about documentation and clarity, and want to improve how people interact with data across the company.

Responsibilities

Maintain and expand the company’s analytical data model using Snowflake and dbt, ensuring datasets are reliable, well-structured, and easy to use.
Partner with stakeholders to understand reporting and analytics needs and translate them into new models and datasets.
Investigate discrepancies in metrics and datasets and perform root-cause analysis across systems.
Monitor and maintain ELT pipelines across our data stack.
Investigate and resolve pipeline failures, schema changes, and data inconsistencies.
Identify opportunities to improve pipeline reliability, efficiency, and cost effectiveness.
Expand documentation across the data model to clearly describe business logic, relationships, and definitions.
Ensure datasets are clearly structured and documented so they can be reliably used across analytics tools and internal workflows.
Contribute to the structured AI data context files that help internal AI tools accurately interpret datasets and metrics.
Help maintain data governance standards, including contributing to PII masking policies and ensuring sensitive customer data is handled appropriately across the data platform.
Work closely with Product, Revenue, and Operations teams to understand their data needs and questions.
Help stakeholders navigate the data model and identify the most appropriate datasets for their use cases.
Occasionally build or modify Hex projects to support data exploration or reporting needs.