Analytics Engineer
Build and maintain Confido's centralized data warehouse and analytics infrastructure. Design scalable data models, establish data standards, and enable self-service analytics across the organization.
About the job
What You'll Do
- Design, build, and maintain our centralized data warehouse and analytics infrastructure.
- Develop scalable data models that power reporting, dashboards, operational workflows, and customer-facing data exports.
- Serve as the steward of Confido's data landscape, creating visibility into data ownership, lineage, and dependencies while ensuring data is discoverable, trustworthy, and easy to consume across the organization.
- Consolidate and standardize data models across multiple products and teams, creating a single source of truth for the business.
- Establish data engineering best practices, including data modeling standards, testing, documentation, monitoring, and governance.
- Partner closely with Engineering, Product, Operations, and Customer teams to define metrics and deliver actionable insights.
- Improve data quality, reliability, and accessibility across the organization.
- Enable self-service analytics by creating scalable datasets and semantic layers for downstream consumers.
What We're Looking For
- Experience building and operating modern data warehouses and analytics platforms.
- Strong SQL skills and experience modeling large datasets.
- Deep experience with distributed data processing, including designing performant ETL pipelines and optimizing large-scale data workloads.
- Experience with data pipeline orchestration, ETL/ELT workflows, and data infrastructure.
- Familiarity with modern analytics tooling such as Snowflake, dbt, or similar technologies.
- Ability to balance immediate business needs with long-term platform investments.
- Excellent communication skills and a track record of working cross-functionally with technical and non-technical stakeholders.
Skills
SQL, Snowflake, dbt, ETL, ELT, Data Modeling, Data Warehousing, Data Pipeline Orchestration, Distributed Data Processing
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