Senior Analytics Engineer

Portage Ventures GP Inc.; United States; Remote; USD 100,000 - 130,000; Full time

Benefits offered by this job

Competitive Salary & Stock Options

Health Benefits

New Hire Home‑Office Setup: One time USD $500

Monthly Stipend: USD $150

Job summary

A leading data platform company is seeking an Analytics Engineer to lead the data transformation initiatives. This role will design and maintain scalable data models using dbt and SQL, collaborating with multiple teams to ensure data quality and integrity. A minimum of 4 years of experience in analytics engineering is required, along with strong SQL and Python skills. The position offers remote work flexibility, competitive salary, stock options, and additional benefits including a monthly stipend for home office setup.

Qualifications

• 4+ years of experience in analytics engineering or data engineering focused on transformation.
• Proven track record of owning end-to-end data products with data quality and scalability.
• Expert-level skills in SQL and dbt for complex queries.

Responsibilities

• Design, build, and maintain scalable data models using dbt and SQL.
• Establish best practices for data modelling, development, testing, and monitoring.
• Collaborate with teams to define requirements and deliver reliable data products.

Skills

Analytics Engineering

Data Transformation

SQL

Python

Data Modeling

Tools

dbt

GCP

Git

Airflow

Job description

About the Role:

We are seeking an Analytics Engineer to own and execute the vision for our data transformation layer. You will be at the heart of our data platform, processing hundreds of millions of events daily from a wide array of sources, including transactional databases, API logs, CRMs, payment systems, and marketing platforms.

You will join a 100% remote team and work closely with Data Engineers, who manage data ingestion, and Data Scientists and Business Users, who consume your data models. Your primary responsibility will be to use dbt and Trino on our GCP‑based, open‑source data infrastructure to build robust, scalable data models.

These models support stakeholders across the company—from finance and operations to the executive team—and are delivered via BI tools, reports, and reverse ETL systems.

What You’ll Do:

• Own the Transformation Layer: Design, build, and maintain scalable data models using dbt and SQL to support diverse business needs, from monthly financial reporting to near‑real‑time operational metrics.
• Set Technical Standards: Establish and enforce best practices for data modelling, development, testing, and monitoring to ensure data quality, integrity (up to cent‑level precision), and discoverability.
• Enable Stakeholders: Collaborate directly with finance, operations, customer success, and marketing teams to understand their requirements and deliver reliable data products.
• Integrate and Deliver: Create repeatable patterns for integrating our data models with BI tools and reverse ETL processes, enabling consistent metric reporting across the business.
• Ensure Quality: Champion high standards for development, including robust change management, source control, code reviews, and data monitoring as our products and data evolve.

What You Need (Must‑Haves):

• 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.
• Technical Versatility:
  • 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).

Nice to Haves:

• Experience with data ingestion tools (e.g., Airbyte) and orchestration tools (e.g., Airflow).
• Domain experience for brokerage operations or a passion for financial markets and modelling financial datasets.

How We Take Care of You:

• 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

Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.