Analytics Engineer, Socure

• 3-5+ years as an Analytics Engineer, Data Engineer, or similar role with a strong analytics orientation
• Strong proficiency with Snowflake and familiarity with AWS analytics services (Redshift, Athena, S3, SageMaker, etc.)
• Expertise in SQL, Python, and Spark for data processing, automation, and custom integrations
• Experience with dbt and modern data modeling best practices
• Hands-on experience with Git-based CI/CD workflows (GitLab preferred)
• Familiarity with ingestion tools such as Fivetran
• Proven ability to translate business requirements and metric definitions into robust, scalable data models
• Strong communication and stakeholder management skills

Desirable

• We are looking for an experienced Analytics Engineer to own and evolve the BI team’s technical infrastructure (Snowflake, dbt, GitLab CI/CD, scheduling frameworks, and ingestion tooling) while ensuring all BI systems and workflows remain fully aligned with the broader Data Engineering architecture and design principles
• This role is responsible for keeping the BI environment scalable, maintainable, and consistent with the company’s overall data platform strategy
• You will collaborate closely with Data Engineering, who manage the source-to-mesh pipelines, and build everything needed to deliver clean, reliable, analytics-ready data into the BI workspace
• This includes developing curated data layers, ensuring pipeline reliability, maintaining governance standards, and enabling efficient downstream analytics across dashboards, reporting, and domain models
• This role is intentionally scoped as an Analytics Engineer, not just a data or platform engineer because success requires:
• Understanding analytics use cases, business metrics, and performance KPIs
• Designing data models that correctly support those metrics and semantic definitions
• Working closely with business stakeholders to gather context and ensure data structures reflect real-world logic
• Balancing technical efficiency with analytical usability, building data assets that analysts and business teams can reliably use for decision-making
• You will serve as the bridge between technical data systems and the analytical needs of the business
• Administer and optimize our Snowflake data warehouse (roles, performance, cost control, governance)
• Maintain and scale dbt projects including core models, tests, documentation, semantic modeling, and deployments
• Manage GitLab pipelines/runners to support robust CI/CD for BI assets
• Oversee job scheduling and orchestration for BI transformations and data flows
• Own ingestion pipelines relevant to BI data needs
• Collaborate with Data Engineering to understand upstream mesh data products with BI analysts to understand business logic, metrics definitions, and performance targets
• Extend mesh data into curated BI data layers optimized for analytics
• Design data structures that support accurate, scalable analytics (fact tables, dimensions, semantic layers)
• Participate in architectural decisions to align upstream pipelines with downstream analytical requirements
• Build custom solutions (APIs, extracts, materialized datasets, governed marts) to deliver data in the right format for each use case
• Implement robust testing, monitoring, and reliability processes for BI pipelines
• Ensure fast, reliable data availability for business stakeholders
• Partner with BI Analysts to maintain a reliable modeling environment and help unblock analytical workflows
• Recommend the most effective data modeling approaches and development processes, considering business priorities and resource limits
• Participate in tooling evaluations and decisions, ensuring solutions fit BI use cases and organizational architecture
• Provide clarity in ambiguous situations and advise leadership on risks, dependencies, and sequencing of work