Senior Data Engineer

Job Title: Senior Data Engineer

Location: Fully Remote (must work Pacific Time hours)

Compensation: $195,000 base salary

Work Authorization: U.S. work authorization required — no sponsorship available

Overview

We are seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data infrastructure that powers analytics, reporting, and data-driven decision-making across the organization. This role is ideal for an engineer who thrives in modern data environments, understands large-scale data architecture, and has deep experience building robust ETL/ELT pipelines within a Lakehouse ecosystem.

You will play a key role in developing reliable data platforms, implementing governance standards, and enabling high-performance analytics through strong data modeling and transformation practices.

This is a fully remote role that requires working Pacific Time business hours.

Key Responsibilities

• Design, build, and maintain scalable ETL/ELT data pipelines supporting analytics and operational workloads.
• Develop and optimize complex SQL transformations and large-scale data processing workflows.
• Implement and manage modern data architectures supporting analytics engineering and self-service reporting.
• Design and maintain robust data models using established methodologies (e.g., Kimball, Data Vault, semantic modeling).
• Optimize query performance and ensure efficient processing of large data volumes.
• Build and maintain Lakehouse architecture components using modern open table formats and distributed query engines.
• Implement and enforce data governance standards, including data quality, lineage, and documentation.
• Collaborate with analytics, product, and data science teams to deliver trusted and scalable data solutions.
• Contribute to platform reliability, monitoring, and performance tuning across the data ecosystem.

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Required Qualifications

• Extensive experience with expert-level SQL and strong Python development.
• Proven experience building robust, production-grade ETL/ELT workflows.
• Advanced experience with Snowflake and dbt Labs (dbt) for data transformation and analytics engineering.
• Deep expertise in modern data modeling techniques, including Kimball, Data Vault, and semantic layer design.
• Demonstrated experience tuning and optimizing performance of large-scale analytical queries.
• Hands-on experience working within Lakehouse architectures using open table formats and distributed query engines (e.g., Iceberg, Trino, or similar technologies).
• Strong experience implementing data governance practices, including data quality frameworks, metadata management, and lineage tracking.