Staff Analytics Engineer

Alpaca

. Design, build, and maintain scalable data models using dbt and SQL for financial reporting and operational metrics.

Posted 9/24/2026full-timeRemoteLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data models using dbt and SQL, with a strong focus on data transformation and quality. Proven ability to collaborate across teams and own data products end-to-end while implementing best practices in analytics engineering.

Highest-signal resume keywords

Expert-Level SQLDbt SkillsPython ProficiencyData Transformation OwnershipCI/CD Workflow Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModellingAnalytics EngineeringETL EfficiencyQuery OptimizationSemantic Layer Modelling

Soft Skills

CollaborationOwnershipAdaptability

Tools & Technologies

GCPAWSAirbyteAirflowGit

Industry Keywords

Financial ReportingOperational MetricsBrokerage OperationsFinancial Markets

Tech Stack

Tools & technologies

AirflowAWSCloudETLGoogle Cloud PlatformPostgresPythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain scalable data models using dbt and SQL for financial reporting and operational metrics.
Establish and enforce best practices for data modelling, development, testing, and monitoring.
Collaborate with finance, operations, customer success, and marketing teams to understand requirements and deliver reliable data products.
Create repeatable patterns for integrating data models with BI tools and reverse ETL processes.
Champion change management, source control, code reviews, and data monitoring as products and data evolve.
Own and execute the vision for the data transformation layer on the company’s data platform.
Work closely with Data Engineers, Data Scientists, and Business Users.

Requirements

What you’ll need

4+ years of experience in analytics engineering or data engineering with a strong focus on the "T" (transformation) in ELT.
Proven track record of owning data products end-to-end, applying analytics and data engineering best practices to ensure data quality, scalability, and robust data models.
Comfortable working with ambiguity and collaborating with stakeholders to define requirements; able to take ownership with minimal oversight in a fast-paced environment.
Experience proactively identifying and implementing improvements to data warehouse performance and ETL efficiency.
Expert-level SQL and dbt skills for complex queries and data transformations.
Proficiency in Python for transformations that extend beyond SQL.
Hands-on experience with query optimization across OLTP and OLAP systems (e.g., Postgres, Iceberg).
Proficiency with Semantic Layer modelling (e.g. Cube, dbt Semantic Layer).
Experience owning CI/CD workflows and establishing team-wide standards for version control and code review (e.g., Git).
Familiarity with cloud environments (GCP or AWS).
Experience with data ingestion tools (e.g., Airbyte) and orchestration tools (e.g., Airflow) is nice to have.
Domain experience for brokerage operations or a passion for financial markets and modelling financial datasets is nice to have.

Benefits

Comp & perks

Competitive Salary & Stock Options
Health Benefits
New Hire Home-Office Setup: One-time USD $500
Monthly Stipend: USD $150 per month via a Brex Card