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Analytics Engineer / Sr. Business Intelligence Engineer - Tourism Economics - Philadelphia
Philadelphia, USPosted 2 months ago
Full-timeonsite
Job Description
Analytics Engineer / Sr. Business Intelligence Engineer - Tourism Economics - Philadelphia
Department: Tourism Economics US
Employment Type: Full Time
Location: Philadelphia, US
Description
Tourism Economics, a subsidiary of Oxford Economics, is looking to hire an Analytics Engineer based in our Wayne, PA office. As an Analytics Engineer, you will serve as the bridge between data engineering, BI, and product while designing scalable data models, building reusable analytical frameworks, and developing the semantic layer that standardizes metrics across the organization. Your work ensures that every insight, whether surfaced in pipelines, models, or dashboards, is accurate, aligned, and trusted.
You will work closely with the Lead Engineer to define modeling logic, metric definitions, and analytical foundations for new product capabilities. You will translate business requirements into technical solutions. You approach data architecture with thoughtfulness and clarity, maintaining a balance between reliability, performance, and simplicity.
Note: Oxford Economics does not offer visa sponsorship for this role, now or in the future. Candidates must be authorized to work in the U.S. on a permanent, ongoing basis without sponsorship.
Note: Oxford Economics does not offer visa sponsorship for this role, now or in the future. Candidates must be authorized to work in the U.S. on a permanent, ongoing basis without sponsorship.
Key Responsibilities
Data Modeling & Infrastructure
- Build and own the data modeling layer in Snowflake using dbt, transforming raw datasets into reliable, well-documented tables and metrics.
- Design scalable, future-proof data structures that support new product features, analytical use cases, and organizational growth.
- Create and maintain the semantic layer that standardizes metrics and enables self-service analytics.
- Automate, monitor, and optimize data pipelines to ensure reliability, version control, and transparent data lineage.
Collaboration & Standards
- Partner with BI engineers to deliver intuitive, performant datasets for dashboards and reporting in tools like Looker, Tableau, or Power BI.
- Work with business stakeholders to gather requirements and translate them into effective, technically sound data solutions.
- Collaborate with data, product, and analytics teams to identify opportunities for data-driven decision-making.
- Implement and maintain QA, testing, and data validation standards across all data models.
- Develop measurement and evaluation frameworks to ensure models meet performance and accuracy expectations.
Documentation & Best Practices
- Maintain comprehensive documentation of data models, business logic, and metric definitions.
- Ensure data assets are discoverable and easy for analysts and stakeholders to use independently.
- Champion best practices and act as a force multiplier through clarity, consistency, and strong data design principles.
- Communicate technical concepts clearly and translate them into actionable insights for non-technical stakeholders.
Skills, Knowledge & Expertise
- 3–6 years as an analytics engineer, BI engineer, or data engineer in a data-driven SaaS or analytics-heavy environment.
- Solid understanding of data modeling principles (Kimball, Data Vault, or modern ELT patterns).
- Strong proficiency in SQL and dbt (required).
- Experience with modern cloud data warehouses (Snowflake, BigQuery, or Redshift).
- Familiarity with orchestration tools such as Airflow, Prefect, or Dagster.
- Working knowledge of Python for transformation, validation, or automation.
- Experience with BI tools such as Looker, Tableau, or Power BI.
What Sets You Apart
- Thoughtful approach to algorithmic and model design—evaluating trade-offs and building solutions that scale cleanly.
- Strong instincts for data product quality, balancing speed, reliability, and reproducibility.
- Business acumen to translate organizational objectives into robust data solutions.
- Excellent communication skills with the ability to make technical concepts accessible to non-technical stakeholders.
- Proven success working cross-functionally with business, product, and technical teams.
Equal Employment Opportunity (EEO)
Oxford Economics is an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, age, religion, sex, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.