Analytics Engineer

Why Socure?

Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.

We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.

We are looking for an experienced Analytics Engineer to own and evolve the BI team’s technical infrastructure (Snowflake, dbt, Git Lab 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 Git Lab 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.

• 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…