Senior Analytics Engineer

It's a great feeling to work for a company that does so much good for others around the world!

This is a 100% onsite role. Remote and/or hybrid arrangements will not be considered.

 

FirstDay Foundation will not be providing employment VISA sponsorship or STEM OPT Extensions for this role.

Position Summary: FirstDay Foundation is seeking an experienced Senior Analytics Engineer to modernize and accelerate our enterprise analytics capabilities. This role is responsible for championing the transformation of organizational data into actionable business intelligence through modern data engineering, analytics, AI-assisted development, executive dashboards, and scalable reporting solutions.

The successful candidate will be technology agnostic—comfortable delivering solutions regardless of the platform. Success is measured by business impact, speed of delivery, and enabling better executive decision-making.

What We’re Looking For: We're looking for someone with a forward-thinking approach to business intelligence. While experience with specific technologies is valuable, we place greater emphasis on curiosity, adaptability, continuous learning, and the ability to deliver measurable business value through innovative data solutions.

The ideal candidate should:
•  Solve business problems before recommending technology.
•  Embrace AI as a force multiplier rather than a future initiative.
•  Deliver working solutions quickly and iterate based on feedback.
•  Adapt as enterprise technologies evolve.
•  Continuously learn and challenge conventional approaches.
•  Balance architectural discipline with pragmatic execution.

Education:  Bachelor’s degree in Industrial Engineering, Business, Information Systems,
 

Experience:

1. Minimum of five (5) years of work experience designing, developing, and delivering enterprise analytics, reporting, or business intelligence solutions.
2. Advanced proficiency in SQL, including complex query development, performance optimization, and data transformation.
3. Experience designing and implementing enterprise-scale dashboards, reports, and executive-level data visualizations.
4. Experience working with modern cloud-based data platforms and enterprise data ecosystems.
5. Demonstrated experience integrating data from multiple systems using APIs, REST services, ETL/ELT processes, or other data integration methods.
6. Strong understanding of dimensional data modeling, data warehousing principles, and analytical 
data architecture.
7. Proven ability to translate complex business requirements into scalable technical solutions and actionable analytics.
8. Excellent written and verbal communication skills, including the ability to present technical concepts to executive and non-technical audiences.
9. Experience partnering directly with senior leadership, business stakeholders, and cross-functional teams to define analytics strategy and deliver business value.
10. Experience collaborating with infrastructure, security, and application teams to establish secure access to enterprise systems, integrate data from multiple sources, and deliver end-to-end analytics solutions.

Preferred Experience:

Experience with one or more of the following technologies or platforms:
• Tableau Next
• Tableau
• Snowflake
• Databricks
• Microsoft Fabric
• Power BI
•  Salesforce Data Cloud
• Microsoft Azure
•  Amazon Web Services (AWS)
• Python
• Git
• dbt

Experience with modern artificial intelligence and advanced analytics technologies, including:

•  AI copilots and generative AI tools
•  Large Language Models (LLMs)
•  Prompt engineering techniques
•  Retrieval-Augmented Generation (RAG) architectures
•  Agentic AI workflows and intelligent automation
•  Machine learning concepts and foundational predictive analytics
 

Duties:

1. Understand the Business: Partner directly with executive leadership and business stakeholders to understand strategic objectives and translate business needs into scalable analytics solutions.
2. Establish Access: Collaborate with infrastructure, security, and application teams to establish secure access to enterprise systems and data sources.
3. Build the E2E Solution: Design, develop, and maintain end-to-end analytics solutions, including data ingestion, integration, transformation, semantic modeling, visualization, and executive reporting.
4. Engineer the Integrations and Data Movement: Design, build, and maintain secure data integrations, automated data exchanges, data synchronization workflows, and enterprise data relays between business systems using APIs, connectors, cloud services, and other integration technologies.
5. Integrate Enterprise Systems: Integrate and manage data across Salesforce, Workday, Acumatica, Microsoft 365, SharePoint, cloud data platforms, and other enterprise applications.
6. Model the Data: Build scalable semantic data models and reusable datasets that promote consistency, governance, and enterprise-wide reuse.
7. Automate Pipelines: Develop and maintain automated data pipelines, reporting workflows, and orchestration processes to improve efficiency, reliability, and delivery speed.
8. Deliver Analytics: Design and deliver executive dashboards, operational reporting, and self-service analytics solutions that drive informed decision-making.
9. Deploy to Digital Displays: Own the publication, deployment, and ongoing operation of executive dashboards and analytics content across web, mobile, and enterprise digital display environments, ensuring information is accurate, current, and reliably displayed to business stakeholders.
10. Apply AI: Evaluate, implement, and optimize AI-assisted analytics capabilities, including copilots, large language models (LLMs), prompt engineering, and intelligent workflow automation where appropriate.
11. Optimize: Monitor and optimize solution performance, data quality, reliability, and governance across the analytics ecosystem.
12. Enable User Adoption: Provide technical leadership and mentorship to team members while enabling business users through self-service analytics, training, and adoption of enterprise reporting standards and analytics engineering best practices.
13. Continuous Improvement: Continuously evaluate emerging analytics technologies and identify opportunities to automate processes, reduce manual effort, and improve analytics capabilities.

Other Responsibilities:

1. Perform other job duties as assigned.

English (United States)

If you like to work with people that believe they can make a difference in the world, this is the company for you!

EEO Statement

In accordance with Title VII  of the Civil Rights Act of 1964 and other applicable federal and state laws (e.g., the Age Discrimination in Employment Act (ADEA), and the Americans with Disabilities Act (ADA), it is our policy to provide equal employment opportunity and treat all employees equally regardless of race, religion, national origin, color, sex, or any other classification made unlawful or prohibited by federal, state and/or local laws, such as age, citizenship status, veteran or military status, or disability. This policy applies to all terms and conditions of employment, including hiring, promotion, demotion, compensation, training, working conditions, transfer, job assignments, benefits, layoff, and termination.

Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

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