Analytics Engineer

Salary

$84,961.00 - $100,000.00

Location

Philadelphia, PA

Posted

Today

The Analytics Engineer is a technical architect within Advancement Prospect Analytics (APA), turning complex institutional data into actionable intelligence for fundraising and alumni relations. The role bridges raw data infrastructure and frontline fundraising strategy by designing, building, and maintaining data products on a modern cloud stack.

The incumbent utilizes Snowflake for data warehousing and Salesforce NPSP for relationship management, engineering integrations that empower 18 schools and central DAR staff to identify and engage Penn's most impactful prospects. The role works across the full analytics workflow: Git for version control and peer review, Asana or JIRA for project tracking, and Qlik Cloud, Snowflake, and Posit Connect for deploying dashboards and predictive models that support the University's fundraising campaigns.

This position reports directly to the Senior Director of Advancement Analytics in Development and Alumni Relations.

Systems Architecture & Data Engineering

Design, build, and troubleshoot system-to-system integrations and automated data pipelines between Snowflake, Salesforce, and external sources—including REST API–based connections, secure authentication (short-lived tokens, key-pair/OAuth), and daily ETL processes with error logging.
Develop and optimize complex SQL queries, views, and middleware to ensure data integrity and high performance across the advancement ecosystem.
Design dimensional data models and transformation layers that turn raw data into strategic fundraising tools and actionable insights.

Development Workflow & Governance

Establish and maintain best practices for code management in Git, including branching strategies, pull requests, and documentation-as-code.
Ensure all analytical scripts (SQL, R, Python) are versioned, audited, and recoverable.
Implement CI/CD principles for analytics to enable reliable, tested, automated deployment of data models.

Project Management & Stakeholder Engagement

Track project milestones, manage backlogs, and communicate project health.
Coordinate requirements gathering for strategic initiatives, translating business needs into technical specifications and transparent timelines.
Advise DAR users on the planning, selection, and implementation of data solutions to address specific business requirements.

Advanced Analytics & AI

Deploy and maintain visualization tools and statistical environments across Qlik Cloud, Snowflake, and Posit Connect.
Leverage Snowflake Cortex AI for data engineering and AI-driven analytics tasks.
Monitor application health and provide technical support to users across Penn's schools and centers.

Note: This role requires substantive, hands-on Snowflake experience. Applicants should be prepared to speak in specific detail about Snowflake projects they have built (e.g., pipelines, data models, warehouse/RBAC configuration) and may be asked to complete a brief technical screening in Snowflake SQL as part of the interview process. Applicants should also be prepared to discuss integrations they have built involving Snowflake connectivity, authentication, and troubleshooting.

Required Education & Experience

Bachelor’s degree and 3–5 years of experience in data engineering, systems analysis, or a related technical field, or an equivalent combination of education and experience.
Minimum 3 years of recent, hands-on, production experience with Snowflake, including warehouse sizing/cost management, RBAC, Streams & Tasks/Dynamic Tables, MERGE-based incremental loading, and stage-based ingestion of semi-structured data (JSON/Parquet/CSV). General SQL experience on other platforms alone does not meet this requirement.
Advanced SQL fluency — complex CTEs, window functions, MERGE, and CTAS — and experience designing dimensional/star-schema data models through reusable, production-grade views.
Python for data engineering: Proficiency in Python for consuming REST APIs, handling authentication and secrets, parsing and transforming structured/semi-structured data (e.g., JSON), and connecting to Snowflake programmatically (e.g., via the Snowflake Connector for Python or SQLAlchemy).
Integration & connectivity engineering: Demonstrated experience building and maintaining production system-to-system integrations, including developing brokering middleware or services to connect systems that cannot integrate natively, and independently diagnosing failures across the stack—including network-layer issues such as IP allowlisting, network policies, and changing provider IP ranges.
Proven experience with Git version control workflows.

Preferred Qualifications

SnowPro Core Certification (or higher) strongly preferred. Candidates without a current certification should be prepared to demonstrate equivalent hands-on Snowflake expertise.
Salesforce NPSP: Experience with Salesforce NPSP (Non-Profit Success Pack) and architecting its schemas within a Snowflake environment.
Project Tooling: Experience managing complex task dependencies in Asana or JIRA.
Stored Procedures: Experience writing stored procedures (SQL, and/or JavaScript or Python) and UDFs for procedural data transformation logic.
Data Sharing & Marketplace: Experience consuming Snowflake Marketplace data products and configuring inbound/outbound Secure Data Shares.
AI & NLP: Experience using LLMs (OpenAI, Anthropic, or open-source equivalents) for AI-driven text processing and analytics; familiarity with Snowflake Cortex AI functions and/or agent-building a plus.
Statistical Programming: Proficiency in R or Python for data mining, statistical inference, and predictive modeling.
Domain Knowledge: Understanding of the Higher Education "Advancement" lifecycle — Prospect Pipeline management, Annual Giving, and Major Gifts — along with gift accounting concepts (e.g., hard vs. soft credit, recognition types).

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