Senior Analytics Engineer

AlphaSense is seeking a Senior Analytics Engineer to join its Data Engineering team. This role is crucial for optimizing existing data models, rebuilding high-impact, reusable models, and enabling scalable analytics. The engineer will design and maintain clean, performant data models, collaborating with Data Engineers, Data Analysts, and business partners to power decision-making. This position is ideal for a product-minded individual who enjoys end-to-end ownership and stakeholder collaboration.

Must Have

• Product-minded analytics professional
• Strong ownership and business curiosity
• Deep expertise in SQL
• Strong hands-on experience with dbt
• Experience with BigQuery
• Version control using Git
• Experience working with or contributing to CI/CD pipelines for analytics workflows

About the Role

We are looking for a Senior Analytics Engineer to join our Data Engineering team. This role sits at the intersection of data modeling, analytics, and business enablement, and plays a critical part in helping Data Analysts and stakeholders work more efficiently with trusted, high-quality data. The team is currently focused on optimizing existing data models, rebuilding high-impact, reusable models, and enabling scalable analytics across the organization. You’ll work closely with Data Engineers, Data Analysts, and business partners to design and maintain clean, performant data models that power decision-making. This is an excellent opportunity for a product-minded analytics engineer who enjoys owning their work end-to-end and collaborating closely with stakeholders.

Who You Are:

You’re a product-minded analytics professional with strong ownership and business curiosity. You bring deep expertise in SQL and dbt, understand how to model data for both performance and usability, and enjoy collaborating with stakeholders to turn requirements into scalable data solutions.

Core Technical Skills

• Advanced SQL expertise, including: Complex transformations Window functions, CTEs Writing optimized, maintainable queries.
• Strong hands-on experience with dbt, including: Project structuring (staging, intermediate, marts), Writing and maintaining dbt tests, Using dbt documentation features, Experience with macros and packages.
• Experience with BigQuery, including: Partitioning and clustering, Performance tuning, Cost optimization strategies.
• Version control using Git.
• Experience working with or contributing to CI/CD pipelines for analytics workflows (e.g., GitHub Actions, GitLab CI).

What You’ll Do:

• Design, build, and maintain dbt models to support analytics and reporting needs across the organization.
• Develop and maintain metrics and source-of-truth data marts to support critical reporrting functions across the organization.
• Develop clean, efficient, and scalable data models in partnership with the Data Architect and Data Engineers
• Implement data quality checks using dbt tests (schema and data tests)
• Create and maintain clear documentation for data models using dbt docs
• Monitor and support data model pipelines, troubleshooting and resolving issues as needed
• Collaborate with Data Analysts and business stakeholders to translate requirements into well-structured data models
• Apply strong data modeling principles to create intuitive and performant data marts
• Contribute to improving standards, best practices, and processes across the Data & Analytics function
• Mentor junior team members and support a collaborative, high-quality engineering culture