Analytics Engineer

Saragossa; Santa Monica (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Saragossa in Santa Monica, CA is seeking an Analytics Engineer to build the data foundation for a growing investment platform. This role shapes architecture, transforms messy data into trusted information, and enables AI-driven analytics.

You’ll work with leaders across Investments, Finance, Operations and more, using SQL and dbt, Snowflake/BigQuery, and ELT to deliver scalable data solutions and automate reporting beyond Excel.

Qualifications

• 5+ years in Analytics Engineering or similar role.
• Expert SQL skills and experience with dbt or equivalent.
• Strong understanding of data architecture and ELT.
• Experience with Snowflake, Databricks, Redshift or BigQuery and cloud platforms (AWS/Azure/GCP).
• Ability to turn messy data into trusted, scalable data products.

Responsibilities

• Build transformation layer using SQL and dbt.
• Create reusable data models and metrics across sources.
• Develop data architecture and ELT processes.
• Consolidate data from multiple sources for trusted reporting.
• Automate reporting and reduce Excel-based processes.
• Collaborate with Finance, FP&A, Accounting, Leasing, Operations and leadership.

Skills

Analytics Engineering

SQL

dbt

Data architecture

ELT

Snowflake

Databricks

Redshift

BigQuery

AWS

Job description

Build the data foundation behind a growing investment platform.

This is an opportunity for an Analytics Engineer who wants to have a real impact on how a business uses data - not simply maintain dashboards or work on someone else’s models.

You’ll join the Data & Analytics team at a growing real estate investment platform and play a key role in building the data foundation that supports Investments, Finance, Operations, Portfolio teams, and leadership. The environment is still being built, which means you’ll have the opportunity to shape the architecture, establish best practices, and see your work become part of the core infrastructure of the business.

You’ll work directly with business leaders to understand how they operate, identify where data and reporting are creating friction, and turn those problems into scalable technical solutions. Rather than receiving requirements and simply executing against them, you’ll have a voice in how problems are solved, what gets prioritized, and how the data environment evolves.

A significant part of your impact will come from taking messy, disconnected data and turning it into something the business can actually trust and use. You’ll build the transformation layer using SQL and dbt, create reusable data models and metrics, bring together data from multiple sources, and develop the underlying structure that enables better reporting, analytics, and eventually AI-driven capabilities.

You’ll also have the opportunity to eliminate a lot of the manual work that exists in the business today. Whether that means replacing Excel-based reporting, automating repetitive processes, or creating a reliable source of truth for financial and operational metrics, you’ll be able to directly improve how teams work.

The role is highly collaborative and gives you exposure well beyond the data team. You’ll partner with Finance, FP&A, Accounting, Leasing, Operations, Investments, and other stakeholders, giving you the opportunity to understand the business from the inside and develop the ability to translate real business problems into technical solutions.

We’re looking for someone with 5+ years of experience in Analytics Engineering, or a similar discipline who is genuinely hands-on. You should have expert SQL skills, strong experience with dbt or a comparable transformation framework, and a solid understanding of data architecture, data modeling, and ELT. Experience with modern platforms such as Snowflake, Databricks, Redshift, or BigQuery and cloud environments such as AWS, Azure, or GCP is important.

We’re also looking for someone who is excited about where data is going. AI is becoming increasingly important to how the organization operates, and you’ll have the opportunity to use these technologies to improve productivity, data quality, and the way teams interact with information.

Real estate experience is a plus, but it’s not required. What matters most is that you’re technically strong, commercially minded, comfortable with ambiguity, and excited by the opportunity to build rather than simply maintain.

If you’re looking for a role where you can own meaningful pieces of the data environment, work directly with the business, build from the ground up, and see a tangible connection between your technical work and business outcomes, this is that opportunity.