Senior Data Engineer

Mux

. Own the Mux data warehouse, ingestion layer, and transformation layer, including architecture, administration, permissions, CI/CD, cost, ingestion standards, and data quality .

Posted 11/4/2026full-timeRemote • United StatesSenior💰 $190,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering with a strong foundation in software engineering, focusing on building and maintaining data ingestion, transformation, and orchestration processes. Proficient in ensuring data quality, governance, and leveraging AI coding tools for automation and efficiency.

Highest-signal resume keywords

Data Engineering ExperienceDeep Hands-On dbt ExperienceExpert SQL SkillsStrong Python ProficiencyCloud Data Warehouse Administration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData TransformationData ModelingDimensional ModelingPerformance TuningCost ManagementAutomationData QualityData GovernanceStatistics

Soft Skills

CollaborationProblem-SolvingCommunication

Tools & Technologies

SnowflakeBigQueryDatabricksFivetranAirbyteMetaplaneMonte CarloElementaryAWSGCP

Industry Keywords

Data WarehouseCI/CDData ContractsData ObservabilityLLM AgentsReverse ETLFinance DataDeveloper ToolsInfrastructure CompaniesBusiness Intelligence

Tech Stack

Tools & technologies

AWSBigQueryCloudETLGoogle Cloud PlatformPythonSnowflakeSQL

About the role

Key responsibilities & impact

Own the Mux data warehouse, ingestion layer, and transformation layer, including architecture, administration, permissions, CI/CD, cost, ingestion standards, and data quality
Build and maintain ingestion from production systems and business tools into the warehouse
Operate orchestration, deployments, environment management, and incident response
Push curated data to Salesforce, NetSuite, and HubSpot
Build semantic models and the data foundation behind internal business-question-answering agents
Help measure whether agents provide correct answers
Keep data accurate, tested, simple, observable, and governed
Reduce technical debt and simplify the codebase
Use coding agents such as Claude Code and Cursor for building, testing, and refactoring
Identify and build agent-based automation for manual data work
Establish standards for AI access, review, and human verification of production data interactions
Partner with Engineering on data production, changes, and retirement
Work with Finance, FinOps, Product, and GTM to prioritize models based on business questions
Participate in engineering-style cycle planning with goals, commitments, and status updates

Requirements

What you’ll need

5+ years of data engineering experience, with a strong software engineering foundation
Built and run a data stack end to end in production, including ingestion, warehouse, transformation, orchestration, and post-launch operations
Deep hands-on dbt experience, including model design, testing, macros, CI, and refactoring large projects
Hands-on experience administering a cloud data warehouse; Snowflake preferred, with BigQuery or Databricks considered
Experience with permissions, performance tuning, and cost management
Experience with data contracts and data observability tooling such as Metaplane, Monte Carlo, or Elementary
Expert SQL and strong data modeling skills, including dimensional modeling, grain, and slowly changing dimensions
Strong Python for pipelines, automation, and tooling
Experience with managed ingestion tools such as Fivetran or Airbyte
Comfort working in AWS or GCP
Real day-to-day use of AI coding tools and understanding of their appropriate use and limitations
Working foundation in analysis and statistics
Commitment to data quality and governance
Bonus: experience with semantic layers, LLM agents over structured data, LLM evaluation, data science, additional data platforms, reverse ETL, finance data, developer tools/API-first/infrastructure companies, or smaller companies with broad ownership
Must be eligible to work in the US

Benefits

Comp & perks

Flexible vacation + 11 company holidays
Weekly no-meeting days + quarterly focus weeks
Competitive health, dental, and vision insurance, including fertility
FSA and HSA available
Short-term and long-term disability insurance
Group life insurance
Travel accident insurance
401(k)
Paid parental leave
Professional Development program
Lunch, internet, & ancillary equipment reimbursements
Competitive annual leave policy (25 days annual leave plus 8 public holidays)
Private medical and dental insurance, and a vision stipend, including fertility
Group life assurance
Matched Pension
Team social events