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Marketing Data Engineer Jobs (NOW HIRING)

Data Engineer

Manhattan, NY

$125K - $150K/yr

Data Engineer Location: New York, NY Employment Type: Full-time Focus: Data Engineering, Snowflake ... Their technology helps marketing teams focus on brand storytelling while AI agents handle the ...

Data Engineer

Manhattan, NY · On-site

$125K - $150K/yr

Data Engineer Location: New York, NY Employment Type: Full-time Focus: Data Engineering, Snowflake ... Their technology helps marketing teams focus on brand storytelling while AI agents handle the ...

Marketing Data Analytics

San Francisco, CA · Remote

$88K - $110K/yr

MUST HAVES: 8+ yrs of IT/Engineering 4-yr Degree (Computer Science or Related) 5+ yrs of Data Analytics, with specific work with Marketing contribution to Partner-Sourced Pipelines 3+ yrs Data ...

$81K - $111K/yr

You will work closely with Analytics, Marketing, Data Science, Product, and Engineering teams to translate business needs into scalable data solutions. You will troubleshoot complex pipeline issues ...

New

Collaborate with data engineering to acquire, join, and validate marketing data from primary and secondary sources (e.g., Google Ads, GA4, Search Console). * Customer & Campaign Insights: Apply ...

Data Engineering Lead (Marketing) Position Description (General role information, job purpose, main objectives of the role) Location: Atlanta, GA Duration: FULL TIME / C2H Mode: Hybrid ( 2 days a ...

$117K - $157K/yr

We are an integrated, cross-functional team of marketers, software engineers, data scientists, and analysts who help the Media team execute highly data-driven marketing campaigns and tactics. As a Sr ...

New

Work hand in hand with Data Engineers and Analytics Engineers to get marketing data into the ... warehouse and modeled. Define requirements, explore raw data, and contribute to data models that ...

Work hand in hand with Data Engineers and Analytics Engineers to get marketing data into the ... warehouse and modeled. Define requirements, explore raw data, and contribute to data models that ...

Senior GCP Data Engineer

Phoenix, AZ · On-site

$105K - $143K/yr

Contract Data Engineering & Pipelines * Design and develop batch and streaming pipelines using ... Integrate pipelines with marketing and analytics platforms * Work with cross-functional teams to ...

Marketing Data Scientist

New York, NY · On-site

$113K - $170K/yr

Partner with media, data engineering, and analytics teams to transform business objectives into actionable measurement strategies. * Deliver insights that drive optimization of media and marketing ...

Showing results 41-60

Marketing Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do marketing data engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for marketing data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is a marketing data engineer?

Marketing Data Engineers are professionals who design, build, and manage data systems that enable marketing teams to collect, process, and analyze large volumes of marketing data. They work at the intersection of data engineering and marketing analytics, ensuring that data pipelines are robust, scalable, and optimized for marketing use cases. Their work helps organizations make informed marketing decisions by providing reliable and accessible data from multiple sources, such as web analytics, CRM systems, and advertising platforms. Marketing Data Engineers often collaborate closely with data analysts, data scientists, and marketers to create solutions that drive business growth.

How do marketing data engineers typically collaborate with marketing teams to drive data-driven campaigns?

Marketing Data Engineers work closely with marketing teams by designing data pipelines that collect and process campaign performance data, ensuring marketers have timely and accurate insights. They often participate in cross-functional meetings to understand campaign goals and translate them into data requirements, dashboards, or reports. This collaboration enables marketers to make informed decisions, optimize strategies, and measure ROI effectively. Regular communication and a clear understanding of marketing objectives are key to ensuring the technical solutions provided align with business needs.

What are the key skills and qualifications needed to thrive as a marketing data engineer, and why are they important?

To thrive as a Marketing Data Engineer, you need strong skills in data modeling, SQL, and data pipeline development, often supported by a degree in computer science, engineering, or a related field. Experience with ETL tools, cloud data platforms (like AWS or GCP), and marketing analytics systems such as Google Analytics is typically required. Excellent problem-solving, communication, and collaboration skills help you translate business requirements into technical solutions and work effectively with marketing teams. These abilities ensure accurate, actionable insights that drive data-driven marketing strategies and business growth.

What is the difference between Marketing Data Engineer vs Data Analyst?

AspectMarketing Data EngineerData Analyst
Primary FocusBuilding and maintaining data pipelines for marketing dataAnalyzing data to generate insights and reports
Skills & CertificationsSQL, ETL, data warehousing, cloud platformsSQL, Excel, data visualization tools
Work EnvironmentData engineering teams within marketing or analytics departmentsBusiness units, marketing teams, or analytics departments
Tools UsedApache Spark, Hadoop, cloud data servicesTableau, Power BI, Excel

The main difference is that Marketing Data Engineers focus on creating and managing the infrastructure for marketing data, while Data Analysts interpret that data to provide actionable insights. Both roles often collaborate but serve distinct functions within data-driven marketing strategies.

More about Marketing Data Engineer jobs

What cities are hiring for Marketing Data Engineer jobs?

Cities with the most Marketing Data Engineer job openings:

What states have the most Marketing Data Engineer jobs?

States with the most job openings for Marketing Data Engineer jobs include:

What are popular job titles related to Marketing Data Engineer jobs?

For Marketing Data Engineer jobs, the most frequently searched job titles are:

Infographic showing various Marketing Data Engineer job openings in the United States as of September 2026, with employment types broken down into 9% Internship, 73% Full Time, and 18% Contract. Highlights an 73% In-person, and 27% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer

Manhattan, NY

$125K - $150K/yr

Full-time

Posted 11 days ago


Job description

Data Engineer

Location: New York, NY
Employment Type: Full-time
Focus: Data Engineering, Snowflake, Data Modeling, AI Data Infrastructure, Marketing Technology

About Our Client

Our client is building an AI-powered platform for marketing leaders.

Their technology helps marketing teams focus on brand storytelling while AI agents handle the operationally intensive work behind the scenes, including data management, analytics, campaign generation, measurement, and reporting.

The platform is built on a proprietary consumer graph covering more than 270M U.S. consumers and thousands of through-time attributes. On top of that data foundation, our client has built agentic systems that help brands unify first-party data, standardize messy datasets, train targeting models, improve campaign performance, and give marketing teams meaningful time back.

The company works with leading consumer brands across sports, financial services, hospitality, real estate, estate planning, and other major categories. They have raised $20M from top-tier investors and are building a deeply technical team with experience across data, AI, marketing, finance, research, and consumer technology.

About the Role

Our client is hiring a Data Engineer to design, operate, and scale the pipelines, storage layers, and standardization systems that power their data product and AI platform.

This role is ideal for someone who is strong in analytics engineering, data modeling, Snowflake-powered warehouses, and resilient data infrastructure. You'll help build and scale the data foundation behind a massive people data product while partnering closely with data scientists, AI engineers, and product teams.

This is a high-ownership role for someone who can build reliable pipelines, improve data quality, support large-scale first-party integrations, and help enable AI and agentic access layers on top of structured data.

What You'll Do

  • Own ingestion, data modeling, and transformation for a large-scale consumer data product

  • Build and improve features, attributes, and pipelines across hundreds of millions of individuals

  • Scale first-party data integrations with sales, marketing, and customer systems of record

  • Support and improve a growing multi-terabyte data footprint

  • Partner with data scientists to productionize complex data pipelines and modeling workflows

  • Improve data quality, reliability, standardization, and scalability across the platform

  • Build data infrastructure that supports AI-powered products and agentic workflows

  • Enable AI and agentic access layers, including natural language retrieval APIs and structured data orchestration

  • Work on data products that directly support major enterprise customer opportunities

  • Build with modern data infrastructure including Snowflake, lakehouse architecture on S3, Dagster, dbt, and AWS

What We're Looking For

  • Strong experience in data engineering, analytics engineering, or data infrastructure

  • Experience owning data modeling and transformations in Snowflake or a similar cloud data warehouse

  • Strong SQL skills and comfort working with large, complex datasets

  • Experience building resilient ingestion pipelines and transformation workflows

  • Experience with tools such as dbt, Dagster, Airflow, or similar orchestration platforms

  • Familiarity with AWS data infrastructure, S3-based lakehouse patterns, or similar cloud environments

  • Strong understanding of data quality, standardization, schema design, and pipeline reliability

  • Ability to partner closely with data scientists and product teams

  • Comfort working in a fast-moving startup environment with high ownership

  • Interest in building data systems that power AI products, marketing intelligence, and agentic workflows

Bonus Experience

  • Experience with consumer data, identity graphs, marketing data, or customer data platforms

  • Experience integrating with sales and marketing systems of record

  • Experience building data products for enterprise customers

  • Experience enabling AI, LLM, or agentic access layers on top of structured data

  • Experience with natural language data retrieval, semantic layers, or structured data orchestration

  • Experience working with multi-terabyte datasets or large-scale people data products

Why This Opportunity

  • Build the data infrastructure behind an AI-native marketing intelligence platform

  • Work on a large-scale proprietary consumer graph covering hundreds of millions of U.S. consumers

  • Partner with strong technical teams across data science, AI, product, and engineering

  • Help scale first-party data integrations for leading consumer brands

  • Build data systems that directly unlock major enterprise customer opportunities

  • Work with modern data tools across Snowflake, dbt, Dagster, S3, and AWS

  • Join a venture-backed company with $20M raised and strong commercial momentum