Associate Director, Data Engineering, Measurement

Description

The company is a media agency with 160 people across offices in Phoenix, Durham, Irvington, and New York City. It serves large brands and works with technology in its planning, activation, and measurement.

You will join the Technology & Analytics team, which turns complex data and new technologies into practical tools that help the whole agency work more efficiently.

This is a senior technical leadership role. You will set the architecture, standards, and direction of the data ecosystem, not only build individual pipelines or platforms.

You will work across data engineering, measurement technology, and business strategy with Analytics, Data Science, Media, Product, Engineering, and Technology leaders.

Responsibilities

• Build reliable, scalable data systems that let the agency collect, connect, structure, govern, and activate data for accurate measurement and better business decisions.
• Define the long-term architecture, technical direction, and standards for the company's data engineering and measurement infrastructure.
• Oversee the design and integration of cloud data warehouses, data lakes, ingestion tools, and transformation frameworks.
• Guide the development of scalable, well-documented data models for attribution, reporting, analytics, and business intelligence.
• Lead pipelines and integrations that support media measurement, attribution, conversion tracking, and performance reporting, including data from advertising platforms, analytics tools, and customer systems.
• Support the design of conversion APIs (CAPI), server-side integrations, and other measurement connections.
• Translate attribution requirements from Analytics, Data Science, and Media teams into reliable data engineering work.
• Set standards for data quality, validation, reconciliation, and consistency across platforms, and guide automated checks, monitoring, alerting, and observability.
• Define expectations for incident management, troubleshooting, root-cause analysis, and issue resolution.
• Oversee ingestion, transformation, and orchestration across the data ecosystem, including APIs, event streams, operational databases, advertising platforms, and external providers.
• Review pipeline performance, storage, and platform costs, and find ways to improve scalability, cut latency, and use cloud resources well.
• Create reusable engineering patterns and improve deployment, testing, and production reliability with engineering teams.
• Work with Technology and Infrastructure teams on security, privacy, and access management.
• Translate business goals and measurement priorities into technical recommendations and engineering roadmaps, and help prioritize work by impact, complexity, and resources.
• Act as a trusted technical advisor and explain capabilities, constraints, risks, and tradeoffs to technical and nontechnical colleagues.
• Mentor and coach data engineers, review architecture, support hiring and onboarding, and set expectations for code quality, documentation, and testing.
• Track emerging data technologies and evaluate new tools against real business problems, while avoiding unnecessary complexity.
• Set success measures for platform work, including data quality, reliability, processing speed, cost, and stakeholder trust.

Requirements

• 8 to 12+ years of professional experience in data engineering, data platform architecture, or a closely related field, including senior technical leadership.
• Extensive experience designing, building, and governing modern cloud data platforms and enterprise-scale pipelines.
• Deep expertise with cloud data warehouses such as Snowflake, BigQuery, Amazon Redshift, or Azure Synapse.
• Experience with data lakes or lakehouse architectures, such as Amazon S3, Azure Data Lake Storage, Delta Lake, or Apache Iceberg.
• Advanced SQL, including complex transformations, query optimization, data modeling, and performance tuning on large datasets.
• Strong Python skills or comparable languages used in data engineering.
• Experience with transformation frameworks such as dbt or equivalent.
• Experience with orchestration and ingestion tools such as Apache Airflow, Dagster, Fivetran, or Stitch, or with custom pipelines.
• Ability to design scalable data models and set standards for schema design, documentation, and governance.
• Experience integrating data from APIs, event streams, operational databases, and external platforms.
• Experience with data quality frameworks, monitoring, observability, alerting, and production incident management.
• Strong understanding of data security, privacy, access controls, and compliance.
• Experience in cloud ecosystems, with AWS preferred and Azure or Google Cloud also relevant.
• Experience designing or supporting data infrastructure for measurement, attribution, reporting, or analytics.
• Familiarity with conversion APIs (CAPI), server-side integrations, and modern digital measurement data flows.
• Ability to weigh architectural tradeoffs across reliability, scalability, performance, cost, and maintainability.
• Experience giving technical direction, reviewing architecture, and mentoring engineers.
• Ability to turn complex business and measurement needs into practical, scalable technical solutions.
• Strong communication skills with both technical and nontechnical stakeholders.
• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or a related field, or equivalent practical experience.
• Preferred: experience in advertising, media, marketing technology, digital measurement, or another data-intensive field.
• Preferred: hands-on experience with Snowflake and AWS-based data infrastructure.
• Preferred: experience integrating data from major advertising and analytics platforms.
• Preferred: familiarity with attribution methods, conversion tracking, and marketing measurement challenges.
• Preferred: experience implementing or supporting Meta Conversions API, Google enhanced conversions, or similar server-side measurement integrations.
• Preferred: understanding of event-level data, identity, and privacy-conscious measurement.
• Preferred: experience with CI/CD pipelines, infrastructure as code, containerization, and automated testing.
• Preferred: familiarity with data catalogs, lineage tools, metadata management, and governance frameworks.
• Preferred: experience supporting data science, advanced analytics, or machine learning workflows.
• Preferred: experience developing platform roadmaps and contributing to technology investment decisions.
• Preferred: experience leading technical teams through platform modernization, architecture changes, or infrastructure scaling.
• You evaluate complex technical problems, make sound architectural recommendations, and balance immediate needs with long-term sustainability.
• You connect technical decisions to measurement needs, operations, and the agency's goals.
• You see how pipelines, models, integrations, and platforms affect each other and design systems people can trust.
• You investigate root causes, weigh tradeoffs, and solve problems with structure and judgment.
• You explain complex technical ideas simply and help teams make informed decisions.
• You build strong relationships across disciplines and lead through expertise and credibility.
• You enjoy developing others through coaching, knowledge sharing, and honest feedback.
• You take ownership of platform outcomes, address risks early, and follow through.
• You keep learning about new technologies and changing measurement needs while staying practical about change.
• You hold high standards for data integrity and set clear standards that others can rely on.
• You take the long view on technical decisions and protect the quality, security, and reliability of the data people use.

Conditions

Hybrid model: you work from the office three days a week, on Tuesday, Wednesday, and Thursday.

You must live in, or be able to commute to, the Irvington, New York office three days a week.

You must be authorized to work in the United States for any employer. The company does not sponsor or help with work authorization at this time.

The company is committed to inclusion and welcomes people with different experiences and perspectives.

Benefits

• The estimated pay range for this role is $120,000 to $150,000. Final pay depends on the skill level and experience you bring.
• Salaries are competitive, benchmarked, and set to keep pay fair across roles, experience, and impact.
• Growth is based on performance, progress, and potential rather than time in role, with ongoing feedback and chances to take on more.
• Flexible paid time off
• Medical, dental, and vision plans
• Parental leave
• Mental health support
• Annual company contribution to a 401(k)
• Flexible Spending Accounts (FSAs) and Healthcare FSA
• Commuter benefits and corporate discounts
• Fertility and family-building support through Carrot
• Employee Assistance Program (EAP)
• Casual work environment, team building, and social events