{"id":3363329,"url":"https://alion.io/job/attention-arc-associate-director-data-engineering-measurement","title":"Associate Director, Data Engineering, Measurement","company":{"id":670368,"name":"Attention Arc","domain":"attentionarc.com","url":"https://alion.io/company/attentionarc","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Irvington, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":120000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Fivetran","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Incident Management","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"CI/CD","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-10-27T18:05:34Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-30T02:47:40Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Technology & Analytics | The Builders and Translators\nWe are a 1,000-piece puzzle. Each of us is essential, interconnected, and intentionally designed. Together, we create something powerful: media that matters, growth that lasts, and a culture we are proud to build.\nAs part of our Technology & Analytics team, you are one of the Builders and Translators, turning complex data, emerging technologies, and innovative ideas into practical solutions that help our entire agency work smarter. You connect human expertise with the power of technology, building the data foundations that power measurement, attribution, reporting, and more intentional decision-making.\nWHAT YOU'LL DO\nAt Attention Arc, we believe technology should amplify human expertise, not replace it. And when it comes to media measurement, that starts with data people can trust.\nAs our Associate Director, Data Engineering, Measurement, you'll help shape how data is collected, connected, structured, governed, and activated across the agency. You'll bring the technical expertise and architectural judgment needed to build reliable, scalable data systems that support accurate measurement, meaningful insights, and better business decisions.\nYou'll work at the intersection of data engineering, measurement technology, and business strategy, partnering with Analytics, Data Science, Media, Product, Engineering, and Technology leaders to ensure our data infrastructure supports how we plan, activate, optimize, and measure media.\nThis is a senior technical leadership role for someone who thinks beyond individual pipelines or platforms. You'll help define the architecture, standards, and technical direction of our data ecosystem, ensuring information moves reliably between systems and can be confidently used for attribution, reporting, optimization, and decision-making.\nYou'll guide the development of scalable data models, oversee data integrations, strengthen governance and quality standards, and help the agency navigate the growing complexity of modern measurement. From cloud data warehouses and data pipelines to conversion APIs and evolving attribution requirements, you'll ensure our technology is built around how data is actually used.\nYou'll also mentor engineers, guide technical decisions, and help teams balance immediate business needs with long-term platform reliability and scalability.\nYour impact will be measured by the trust our people place in our data, the strength and scalability of our measurement infrastructure, and the clarity our systems bring to increasingly complex media decisions.\nKey Responsibilities\nData Platform Architecture & Technical Leadership\nHelp define and guide the long-term architecture, technical direction, and evolution of Attention Arc's data engineering and measurement infrastructure.\n\nOversee the design and integration of modern data platforms, including cloud data warehouses, data lakes, ingestion tools, and transformation frameworks.\n\nEstablish and maintain technical standards for data modeling, schema design, pipeline development, access controls, and platform governance.\n\nGuide architectural decisions that balance scalability, reliability, performance, cost, and maintainability.\n\nEvaluate existing data infrastructure and identify opportunities to simplify architecture, reduce technical debt, and improve operational efficiency.\n\nEnsure data platforms can support evolving business needs, measurement methodologies, and increasing data complexity.\n\nPartner with Technology and Infrastructure teams to maintain appropriate security, privacy, and access management practices.\n\nProvide hands-on technical guidance and contribute directly to complex engineering challenges when needed.\n\nMeasurement Data Engineering & Attribution Infrastructure\nGuide the development and maintenance of data pipelines and integrations that support media measurement, attribution, conversion tracking, and performance reporting.\n\nOversee the collection, transformation, and organization of measurement data from advertising platforms, analytics tools, customer systems, and other relevant sources.\n\nSupport the design and implementation of conversion APIs (CAPI), server-side data integrations, and other measurement connectivity solutions.\n\nPartner with Analytics, Data Science, and Media teams to understand attribution requirements and translate them into reliable data engineering solutions.\n\nEnsure measurement data is structured and documented to support consistent reporting, analysis, and optimization.\n\nHelp address challenges related to data discrepancies, incomplete signals, platform limitations, and evolving measurement requirements.\n\nDevelop scalable approaches to integrating data from multiple advertising platforms, client systems, and third-party sources.\n\nSupport the agency's ability to connect media activity with meaningful business outcomes through accurate, accessible, and well-governed data.\n\nData Modeling, Quality & Governance\nOversee the design and development of scalable, well-documented data models supporting attribution, reporting, analytics, and business intelligence.\n\nEstablish standards for data quality, validation, reconciliation, and consistency across platforms and datasets.\n\nGuide the implementation of automated data quality checks, monitoring, alerting, and observability practices.\n\nEnsure data pipelines are reliable, resilient, and appropriately monitored.\n\nDevelop clear expectations for incident management, troubleshooting, root-cause analysis, and issue resolution.\n\nPromote consistent data definitions, documentation, and lineage to strengthen trust and reduce ambiguity.\n\nPartner with Technology and business stakeholders to ensure data governance practices support security, privacy, compliance, and responsible use.\n\nBalance immediate delivery requirements with long-term data integrity, maintainability, and sustainability.\n\nData Integration, Performance & Platform Optimization\nGuide the development and optimization of data ingestion, transformation, and orchestration processes across the agency's data ecosystem.\n\nOversee integrations involving APIs, event streams, operational databases, advertising platforms, and external data providers.\n\nEvaluate pipeline performance, data processing efficiency, storage strategies, and platform costs.\n\nIdentify opportunities to improve scalability, reduce latency, and optimize cloud infrastructure utilization.\n\nEstablish reusable engineering patterns and integration approaches that improve consistency across projects.\n\nCollaborate with engineering teams to improve deployment processes, testing practices, and production reliability.\n\nSupport the evaluation and implementation of new data technologies, frameworks, and architectural approaches.\n\nEnsure platform improvements are aligned with measurable business and operational needs.\n\nCross-Functional Strategy & Business Alignment\nPartner with Data Science, Analytics, Media, Product, Engineering, IT, and Infrastructure leaders to understand current and future data requirements.\n\nTranslate business objectives and measurement priorities into technical recommendations, platform enhancements, and engineering roadmaps.\n\nServe as a trusted technical advisor on how data should be structured, accessed, integrated, and interpreted.\n\nCommunicate technical capabilities, constraints, risks, and architectural tradeoffs clearly to both technical and nontechnical stakeholders.\n\nHelp prioritize engineering initiatives based on business impact, technical complexity, scalability, and available resources.\n\nAlign teams around shared data standards, definitions, and quality expectations.\n\nIdentify opportunities to improve how data moves between strategy, activation, optimization, and measurement.\n\nSupport initiatives that strengthen the agency's ability to make intentional, data-informed decisions.\n\nTechnical Mentorship & Team Development\nProvide technical guidance, coaching, and mentorship to data engineers and other technical team members.\n\nHelp strengthen engineering judgment, architectural thinking, and problem-solving capabilities across the team.\n\nEstablish clear expectations for code quality, documentation, testing, and technical ownership.\n\nParticipate in architectural reviews, technical discussions, and solution design.\n\nSupport hiring, onboarding, and professional development of data engineering talent.\n\nEncourage knowledge sharing, constructive feedback, and collaborative problem-solving.\n\nFoster a culture of accountability, curiosity, and continuous improvement.\n\nLead through expertise, collaboration, and influence, helping others make sound technical decisions.\n\nInnovation & Continuous Improvement\nStay informed about emerging data engineering technologies, measurement capabilities, cloud architectures, and industry best practices.\n\nEvaluate new platforms, tools, and frameworks based on their ability to solve meaningful business problems.\n\nAnticipate future data volume, integration complexity, governance requirements, and measurement needs.\n\nIdentify opportunities to improve data reliability, performance, accessibility, and operational efficiency.\n\nExplore how automation and AI-assisted capabilities can strengthen data engineering workflows and platform monitoring.\n\nRecommend thoughtful architectural improvements that support long-term scalability without introducing unnecessary complexity.\n\nEstablish meaningful success measures for platform initiatives, including data quality, reliability, processing performance, cost efficiency, and stakeholder trust.\n\nHelp build a data ecosystem where every improvement strengthens the agency's ability to make better decisions.\n\nWHAT YOU'LL BRING\nExperience & Technical Expertise\n8-12+ years of professional experience in data engineering, data platform architecture, or a closely related technical discipline, including experience providing senior-level technical leadership.\n\nExtensive experience designing, developing, and governing modern cloud-based data platforms and enterprise-scale data pipelines.\n\nDeep expertise with cloud data warehouses such as Snowflake, BigQuery, Amazon Redshift, or Azure Synapse.\n\nExperience working with data lakes or lakehouse architectures, including technologies such as Amazon S3, Azure Data Lake Storage, Delta Lake, or Apache Iceberg.\n\nAdvanced proficiency in SQL, including complex transformations, query optimization, data modeling, and performance tuning across large datasets.\n\nStrong experience with Python or comparable programming languages used in data engineering and pipeline development.\n\nExperience using transformation frameworks such as dbt or equivalent technologies.\n\nExperience with orchestration and ingestion tools such as Apache Airflow, Dagster, Fivetran, Stitch, or custom-built data pipelines.\n\nDemonstrated ability to design scalable data models and establish standards for schema design, documentation, and data governance.\n\nExperience integrating data from APIs, event streams, operational databases, and external platforms.\n\nExperience with data quality frameworks, monitoring, observability, alerting, and production incident management.\n\nStrong understanding of data security, privacy, access controls, and compliance requirements.\n\nExperience working within cloud ecosystems, with AWS preferred and Azure or Google Cloud also relevant.\n\nExperience designing or supporting data infrastructure used for measurement, attribution, reporting, or analytics.\n\nFamiliarity with conversion APIs (CAPI), server-side integrations, and modern digital measurement data flows.\n\nDemonstrated ability to evaluate architectural tradeoffs involving reliability, scalability, performance, cost, and maintainability.\n\nExperience providing technical direction, reviewing architecture, and mentoring other engineers.\n\nAbility to translate complex business and measurement requirements into practical, scalable technical solutions.\n\nStrong communication skills and experience partnering wit...","description_format":"text","description_chars":20785,"description_truncated":true,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Equity","Hybrid work","Parental leave","Professional development"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Advertising","Creative Agencies"],"lifecycle":[{"event":"open","at":"2026-10-27T22:08:46Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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