Senior Data Engineer – Marketing Analytics

Location: Remote; optional onsite work in Menlo Park, CA
Contract: 12-month W-2 contract
Pay: $75–$85 per hour, based on experience
Employment Partner: Russell Tobin

Russell Tobin is supporting a leading global technology organization in hiring a Senior Data Engineer to help build scalable data pipelines, automated reporting solutions, and analytics infrastructure for a high-impact growth marketing team.

This role is ideal for a data engineering professional who also has strong analytical and stakeholder-facing capabilities. The successful candidate will have experience working with very large datasets, building production-level pipelines, and using SQL to turn complex data into actionable insights.

Responsibilities

• Collaborate with growth marketers, program managers, analytics teams, and cross-functional stakeholders to define data and reporting requirements.
• Design, build, and maintain scalable data pipelines that support marketing campaigns and analytics initiatives.
• Develop and optimize ETL processes for data extraction, ingestion, transformation, and processing across multiple data sources.
• Build automated reports, dashboards, and recurring analyses that enable data-driven decision-making.
• Write high-quality, efficient SQL queries to retrieve, transform, and analyze large datasets.
• Create reporting and visualization solutions using Tableau or similar business intelligence platforms.
• Automate campaign reporting and improve the scalability and reliability of marketing analytics workflows.
• Identify, investigate, and resolve data integrity, data quality, and reporting accuracy issues.
• Guide team members and stakeholders on data pipeline standards, architecture, and engineering best practices.
• Independently manage projects, communicate timelines, set expectations, and drive work through completion.
• Partner with technical and nontechnical stakeholders to translate business questions into scalable data solutions.

Required Qualifications

• Bachelor’s degree in a STEM or STEAM-related field.
• 5+ years of professional experience using SQL with technologies such as Oracle, Vertica, Hive, MySQL, or similar platforms.
• Proven experience building, operating, and optimizing large-scale data pipelines.
• Experience processing datasets containing millions of rows from multiple sources.
• Strong experience with ETL design, implementation, automation, and maintenance.
• Experience building automated reports and dashboards using Tableau, MicroStrategy, or similar business intelligence tools.
• Professional experience using Python and/or R for data processing and analysis.
• Experience working within an AI-focused organization or using AI tools in a professional data or analytics environment.
• Ability to independently design pipeline solutions and guide teams on engineering best practices.
• Demonstrated leadership, initiative, and ownership of technical projects.
• Strong written, verbal, and interpersonal communication skills.
• Ability to work effectively in a fast-changing environment with evolving or ambiguous requirements.

Preferred Qualifications

• Experience supporting growth marketing, campaign analytics, or marketing operations teams.
• Background working within a large technology company or another organization managing high-volume, complex datasets.
• Experience combining data engineering expertise with business analysis and data visualization.
• Proven ability to self-manage projects, establish timelines, and set clear stakeholder expectations.
• Experience partnering directly with marketers, program managers, analysts, and other business stakeholders.

Ideal Candidate Profile

The ideal candidate is a senior-level data engineer with strong analytical instincts. This person has a demonstrated history of building scalable, production-level pipelines, writing advanced SQL, and supporting business teams through automated reporting and actionable analysis.

Candidates whose experience is limited to small datasets, ad hoc reporting, or small-scale pipelines are unlikely to be successful in this position. Large-scale data engineering experience is essential.

What Success Looks Like

• Reliable and scalable pipelines that support high-volume marketing initiatives.
• Accurate, automated dashboards and reporting workflows.
• Improved data quality and faster resolution of reporting discrepancies.
• Clear technical guidance and best practices for partner teams.
• Strong ownership of projects from requirements gathering through delivery.

Interview Process

The interview process is expected to include up to three stages:

1. Initial screening
2. Technical interview
3. Cross-functional interview with a growth marketing stakeholder