Sr Analytics Engineer

About Cority Cority helps customers see and prevent risks across their operations in real time. Our EHS+ platform converges people, data, and AI agents to provide a clear view of information people can trust, automate workflows that make people more impactful, and deliver personalized insights and expertise to improve decision-making. While most solutions respond to risks one at a time, Cority helps prevent them across environmental management, employee health, safety, quality, and sustainability. For 40 years, Cority has been the market leader in EHS+, recognized by top analysts and trusted by more than 1,500 of the most complex organizations worldwide. Cority has received many awards for its strong employee culture and outstanding business performance. To learn more, visit www.cority.com.  About the Team: We are a newly formed analytics team on a mission to make data a first-class citizen across the business. We partner closely with Marketing, Sales, Finance, and Operations to surface insights that drive real decisions — and we’re building the infrastructure to do it at scale. This is a greenfield opportunity to shape how our data platform grows from the ground up. About the Role As our Senior Analytics Engineer, you will own the data platform end-to-end — from raw ingestion to business-ready models. You will architect and lead the build-out of our Medallion architecture (Bronze, Silver, Gold), establishing the standards, patterns, and pipelines that the entire organization will rely on. This is not a maintenance role. You will be the technical anchor for our data infrastructure, a strategic partner to business stakeholders, and a force-multiplier for the analysts working alongside you. If you thrive in a high-ownership environment and want to leave a lasting mark on how a company uses data, this is your role. Responsibilities:

Medallion Architecture Leadership: Lead the design and implementation of a scalable Medallion architecture (Bronze, Silver, Gold), defining ingestion, transformation, and serving layer standards to ensure data quality and reliability across all domains.

Cross-Functional Collaboration: Act as the primary technical liaison between data and business teams, translating ambiguous requirements from Marketing, Sales, Finance, and Operations into well-scoped, scalable data solutions.

Data Modeling: Develop robust data models to identify data gaps and establish analytical layers, including standardized metrics, dimensions, and business logic.

Data Pipeline Management: Design, develop, and maintain end-to-end data transformation pipelines using tools such as Fivetran and dbt.

Infrastructure Optimization: Ingest data from application DBs, event streams, and APIs into a centralized Snowflake data warehouse.

Performance Tuning: Optimize storage and query performance, including tuning schemas and SQL for large-scale datasets.

Quality & Observability: Implement best practices for data quality, monitoring, and observability through tests, alerts, and lineage.

Stakeholder Enablement: Collaborate with Business Analysts to maintain and troubleshoot data models to ensure analytical needs are met.

Documentation: Drive the documentation of data schemas, pipeline architecture, and runbooks.

Qualifications:

Professional Experience: 7+ years of experience as a Senior Analytics Engineer or Senior Data Engineer building pipelines, developing data models, and improving BI infrastructure, ideally at a SaaS company.

Core Stack: Expert-level knowledge of SQL and Python.

Platform Expertise: Expert-level knowledge in Snowflake, Azure, Fivetran, and dbt.

Orchestration: Hands-on expertise with at least one orchestration framework such as Airflow, Prefect, or Dagster.

Technical Skills: Solid understanding of data modeling concepts, specifically star schemas and normalized vs. denormalized structures.

Medallion Architecture: Proven experience designing and leading the implementation of a Medallion (Bronze/Silver/Gold) architecture, with a deep understanding of layered data transformation patterns and best practices for building scalable, maintainable data platforms.

Workflow Development: Experience building ELT/ETL workflows and integrating APIs or webhooks.

Analytical Mindset: Proven ability to translate ambiguous business questions into structured analyses.

Soft Skills: Excellent communication skills with the ability to articulate technical problems to non-technical audiences.

Agility: Comfortable working in an agile environment.

Education: Bachelor's Degree in Engineering, Computer Science, or equivalent.