Senior Data Engineer

Kindsight builds technology that helps fundraisers make a difference.

For decades, Kindsight has supported the education, healthcare, and nonprofit sectors with fundraising tools and the largest charitable giving database on the market.

And as the giving sector evolves, so does Kindsight.

As the leader in fundraising intelligence, Kindsight leverages real-time data and AI to help thousands of organizations around the world identify, manage, and engage with donors—at any scale.

With purpose-built CRMs that corral all of that donor information and campaign tracking into one place, donor prospect research tools that offer proactive insights and real-time donor intel, and generative AI that creates personalized, meaningful content drafts at scale, Kindsight’s product suite is truly changing the game for donor fundraising.

POSITION DESCRIPTION SUMMARY Kindsight seeks a data engineer to join our Product Engineering team.

In this role, you'll work on our Client Data Platform (CDP) and analytics platform, applying software engineering practices to empower institutions in fundraising and athletic operations.

Affinaquest analyzes client data to uncover actionable insights that drive our clients’ missions forward.

You'll work with Snowflake, dbt, Python, and Airflow to enhance and evolve our data stack.

Kindsight is looking for someone with a strong software engineering background, fluent in modern tooling and open frameworks, who will collaborate with Product Engineering peers and client innovation partners to shape our platform’s evolution and deliver value to clients.

In this role, you'll be a strong contributor to architecture, design, and implementation for all phases of our data pipelines.

You will collaborate with software engineers and data scientists to assure data availability and correctness, contributing to a unified approach in delivering solutions.

If you're passionate about writing code, have a pragmatic problem-solving approach, love learning new technologies, and meet our mandatory requirements, we want you on board!

KEY RELATIONSHIPS Reports to :

• Sr Manager of Product Engineering Other key relationships :  Product Leaders, and the Product Delivery Team MANDATORY REQUIREMENTS TO APPLY A Bachelor's degree in computer science, engineering, or relevant equivalent experience.
• Experience in software development best practices, including rigorous unit testing and code review processes. 5+ years of professional experience with advanced data manipulation, including expertise in window functions, common table expressions, and similar techniques. 3+ years of Python.
• Experience in Pandas, DBT, and Airflow preferred. 3+ years of hands-on experience with data warehousing, ideally Snowflake relational data tables, and working with data from diverse sources. 3+ years of experience in building and maintaining data pipelines between SQL databases, API calls, flat files, and external sources.
• US-Based KEY RESPONSIBILITIES Utilize Airflow for workflow automation and orchestration of data pipelines.
• Perform data warehousing functions within Snowflake and transform data using dbt.
• Ability to collaborate effectively with software engineers and data scientists, ensuring data accuracy and availability.
• Strong comprehension of the complete lifecycle of data engineering, from development through maintenance and monitoring, particularly with DBT, Snowflake, and Airflow Hands-on experience with optimizing, and configuring data engineering environments, Kubernetes hosted preferred.
• Knowledge or experience in ticketing data, the sports domain, or retail analytics, adding valuable insights to data processes.
• System-level design and implementation of ETL / ELT pipelines, feature engineering, and effective data management.
• Data visuatation with Tableau dashboards and a strong aptitude for tracking key performance indicators (KPIs).
• Drive innovation and contribute to our client’s success with impactful data solutions.
• Integrate and optimize data engineering workflows with Azure AI services to enhance data-driven decision-making and machine learning model performance.
• IDEAL ATTRIBUTES AND PROVEN CAPIBILITIES Snowflake, dbt, airflow, Azure DevOps, and Github Experience with advancement / fundrasining, ticketing data, the sports domain, or retail analytics Technical curiosity for uncovering hidden metrics and statistical insights.
• You enjoy understanding the data and finding meaningful related untapped value from the data.

Tableau dashboards and KPI tracking POSITION LOCATION Remote or Corporate Headquarters  ( ASU SkySong, Scottsdale, AZ )-  Hybrid Office Policy :