(Senior) Analytics Engineer

tubescience52; Los Angeles (CA); On-site; USD 110,000 - 165,000; Full time

Job summary

TubeScience Labs in Los Angeles (in person) is seeking a (Senior) Analytics Engineer to own data systems that connect ad performance to creative decisions. You’ll work across ingestion, modeling in Snowflake, metrics definition, and reporting via Power BI and related tools.

You will join a small senior team, directly impacting analytics and ML-ready data pipelines. Strong SQL/Python, cloud (AWS/GCP) and GitHub workflows are essential; prior experience with advertising data is preferred.

Qualifications

• 5+ years in analytics engineering or data engineering with ownership of production data systems.
• Experience pulling advertising data from platforms such as Meta, TikTok, Google or Snapchat.
• Strong SQL and Python with ability to translate source APIs to metrics/reports.
• Experience designing data models and warehouse architecture.
• Built or maintained orchestrated pipelines with reliable data quality.
• Developed Power BI reports and semantic datasets with stakeholders.
• Familiar with GitHub-based development and cloud infrastructure (AWS/GCP).
• Ability to autonomously investigate problems and explain trade-offs.

Responsibilities

• Build and evolve the data platform from ingestion to BI and application delivery.
• Ingest advertising data from Meta, TikTok, Google, Snapchat via APIs, handle pagination and backfills.
• Create Snowflake models and document business metrics.
• Maintain Power BI reporting and link ad outcomes to creative decisions.
• Investigate discrepancies, improve pipeline reliability and add checks/observability.
• Collaborate with data, product, engineering and business teams on analytics and ML approaches.

Skills

Analytics engineering

Advertising data

SQL

Python

Data modeling

Power BI

GitHub development

AWS/GCP

Observability

Tools

Power BI

Snowflake

Databricks

Airflow

Coalesce

DBOS

GitHub

Job description

(Senior) Analytics Engineer

TubeScience Labs: Los Angeles, in person - $110,000-$165,000

TubeScience Labs' mission is to create trusted, scalable, and self-improving AI systems that power the largest performance-based paid social creative video company in the world.

TubeScience is Meta's largest creative partner and AppLovin's #1 creative partner, producing 8,000+ original ads every month from a 100,000 sq. ft. Los Angeles studio, backed by a library of 1.6 million+ performance ads and $3B in annual managed ad spend. That is what gives TubeScience one of the richest first-party creative-performance datasets anywhere.

Labs turns that data - and the playbook behind billions in spend - into frontier AI tools that actually ship. We are an AI-native lab working end to end, from research and design to coding, experimentation and delivery. Our pipelines run against real creative, real deadlines, and real budgets every day.

You'll join a small, AI-empowered, senior team of engineers and product managers, with direct access to expert users and full ownership of the systems you build. You'll be expected to use the latest frontier and open-weight models in every phase of the job, from discovery and prototyping to building, testing and deployment.

The role

You'll build the data systems that connect ad performance to creative decisions. Our platform brings together data from advertising channels, creative production workflows and business operations, and your work makes that data reliable, understandable and useful in reports, internal products, and future analytics and machine learning applications.

The role is hands-on across the whole data lifecycle: extracting data from APIs, maintaining dependable pipelines, modeling data in Snowflake, defining metrics, and delivering insights through Power BI and other tools. Much of the foundation already exists. You'll learn how its parts fit together, make it faster and more reliable, and help shape what we build next.

We weigh directly relevant experience heavily. This platform carries real advertising data and feeds the reporting the business runs on from the first week, so tell us plainly where your background maps: advertising data, warehouse modeling, pipelines or BI.

We are open to hiring at Analytics Engineer or Senior Analytics Engineer level, depending on experience and scope of ownership.

Responsibilities

• Build and evolve the data platform, from external sources through ingestion, transformation and curated models to BI and application delivery
• Extract and integrate advertising data from Meta, TikTok, Google and Snapchat using their APIs and Python, handling pagination, rate limits, backfills, schema changes and reconciliation with the platforms
• Build performant Snowflake models, and define and document the metrics the business relies on together with stakeholders
• Maintain and improve Power BI reporting, including a possible migration to a better BI tool, and build datasets that link ad outcomes to creative strategy and production decisions
• Investigate discrepancies and pipeline failures, add checks and observability, and use agents to automate the repetitive work
• Work with data, product, engineering and business partners on analytics and machine learning approaches that feed ad performance back into creative development

Minimum qualifications

• You have 5+ years in analytics engineering, data engineering or a closely related role, with meaningful ownership of production data systems.
• You have worked with advertising or marketing performance data, ideally pulling it directly from platforms such as Meta, TikTok, Google or Snapchat.
• You are strong in SQL and Python, and you can reason through the full path from a source API to a business-facing metric or report.
• You have designed data models and warehouse architecture that support changing business needs, including layered approaches such as medallion architecture where useful.
• You have built or maintained orchestrated pipelines, and you understand failure recovery, backfills, data quality and operational reliability.
• You have developed Power BI reports or semantic datasets, and you have worked with stakeholders to resolve ambiguous metric definitions.
• You are comfortable with GitHub-based development, code review, and cloud infrastructure on AWS or GCP.
• You investigate problems independently, make practical engineering decisions, and explain the trade-offs to technical and business partners alike.

Preferred qualifications

• You have worked on creative analytics, attribution or cross-platform performance measurement.
• You have optimized Snowflake or Databricks performance, including dynamic tables.
• You have used transformation tools such as Coalesce and orchestration tools such as DBOS or Airflow.
• You have built datasets or features for internal applications, experimentation or machine learning.
• You use AI-assisted development fluently, while applying your own judgment to system design, correc