(Senior) Analytics Engineer

TubeScience • Los Angeles, CA

7d • $110,000 - $165,000 • Onsite

About The Position

TubeScience Labs is hiring an Analytics Engineer or Senior Analytics Engineer to build and improve data systems that connect advertising performance to creative decisions. The platform brings together data from advertising channels, creative production workflows, and business operations, making it reliable and useful for reports, internal products, and future analytics and machine learning applications. The role spans the data lifecycle, including API extraction, dependable pipelines, Snowflake modeling, metric definition, and insight delivery through Power BI and other tools. The data foundation already exists in part; the engineer will learn how its components fit together, improve performance and reliability, and help shape future development. The position is based in person in Los Angeles. Level will depend on experience and scope of ownership.

Requirements

• At least 5 years in analytics engineering, data engineering, or a closely related role, with meaningful ownership of production data systems.
• Experience with advertising or marketing performance data, ideally obtained directly from platforms such as Meta, TikTok, Google, or Snapchat.
• Strong SQL and Python skills and ability to reason through the full path from a source API to a business-facing metric or report.
• Experience designing data models and warehouse architecture to support changing business needs, including layered approaches such as medallion architecture where useful.
• Experience building or maintaining orchestrated pipelines and understanding failure recovery, backfills, data quality, and operational reliability.
• Experience developing Power BI reports or semantic datasets and working with stakeholders to resolve ambiguous metric definitions.
• Comfort with GitHub-based development, code review, and cloud infrastructure on AWS or GCP.
• Ability to independently investigate problems, make practical engineering decisions, and explain trade-offs to technical and business partners.

Nice To Haves

• Experience with creative analytics, attribution, or cross-platform performance measurement.
• Experience optimizing Snowflake or Databricks performance, including dynamic tables.
• Experience with transformation tools such as Coalesce and orchestration tools such as DBOS or Airflow.
• Experience building datasets or features for internal applications, experimentation, or machine learning.
• Fluent use of AI-assisted development, with sound independent judgment about system design, correctness, and production changes.

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 APIs using Python; handle pagination, rate limits, backfills, schema changes, and reconciliation with platform-reported data.
• Build performant Snowflake models and define and document business metrics with stakeholders.
• Maintain and improve Power BI reporting, consider a possible migration to a better BI tool, and build datasets linking ad outcomes to creative strategy and production decisions.
• Investigate discrepancies and pipeline failures; add checks and observability; and use agents to automate repetitive work.
• Work with data, product, engineering, and business partners on analytics and machine learning approaches that feed ad performance back into creative development.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed