Global M&C Portfolio Data Engineering Chapter Lead - MarTech Data Architect

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What You'll Do The MarTech Data Architect & Data Engineering Chapter Lead for Marketing & Communications is a senior technical leader responsible for the engineering excellence, architectural integrity, and continuous evolution of BCG's marketing data foundation and connected platforms. Sitting within the MarTech Engineering team, this person leads the data engineering chapter that serves BCG's Global Marketing analytics and data functions owning the technical standards, pipeline architecture, and data platform capability that underpins the full marketing analytics and data ecosystem, from CRM data operations and audience segmentation through to Tableau dashboard delivery, channel performance intelligence, and AI-assisted insight generation. A core part of this ownership is the identity resolution model the framework that matches and unifies client and contact records across marketing data and CRM systems into a single trusted profile. The Chapter Lead designs, manages, and continually refines this model, and partners closely with BCG's core data architect, client, marketing, CRM and engineering teams and data functions to maintain a shared, consistent definition of identity across systems. This role also carries direct responsibility for aligning the marketing data layer with BCG's wider enterprise data approach. The Chapter Lead partners with enterprise data governance and architecture teams to ensure marketing's data standards, access controls, lineage, and quality practices are built to firm-wide policy rather than developed in isolation representing marketing's needs in enterprise governance forums while bringing enterprise requirements back into the marketing data roadmap. The role sits at the intersection of technical leadership and marketing analytics product delivery. The Chapter Lead is not only the most senior data engineering voice they are an active partner to the product owners, analysts, and insight leaders whose work depends on the reliability, quality, and sophistication of the data infrastructure this person builds and leads. They lead and develop the data engineering team, set the data engineering direction in line witht the overall MarTech strategy and standards, establish the data standards, and ensure that BCG's marketing data platforms are capable of supporting not just today's analytics needs but the agentic intelligent data environment the marketing organization is building toward. Chapter Leadership & Data Engineering Development Lead the data engineering chapter serving BCG's Global Marketing & Communications team setting technical direction, establishing engineering standards, and creating an environment where engineers across squads are developing their skills, doing their best work, and growing their careers Provide architectural oversight and hands-on review of engineering work across the chapter code quality, architectural consistency, pipeline reliability, and data modeling standards are upheld across all squads the chapter serves Actively mentor and develop chapter engineers conducting regular technical reviews, providing structured feedback, identifying growth opportunities, and building the collective engineering capability that allows the chapter to take on increasingly sophisticated data and AI challenges over time Partner with squad product owners to ensure engineering capacity, technical priorities, and sprint commitments are aligned with the analytical products and insight capabilities the marketing organization depends on Contribute to hiring decisions, team structure, and data engineering development helping build a chapter that is technically excellent, well-motivated, and capable of sustaining the marketing analytics function's growing ambitions Data Pipeline Architecture & Engineering Design, document, and implement robust, scalable data pipelines that feed the marketing analytics data models powering BCG's dashboard suite, channel insight products, audience intelligence, and CRM data operations built on Snowflake, dbt, and Apache Airflow as the core platform stack Build monitoring and alerting for match-rate quality, pipeline failures, and unexpected shifts in merge/split volume Establish a lineage trail so any resolved identity can be traced back to its contributing source records and the logic that merged them Build processes to handle un-merging (splitting incorrectly merged records) as well as merging Implement data standardization logic (name normalization, address formatting, email canonicalization) as a pre-processing layer ahead of matching Integrate data from across BCG's marketing technology ecosystem into the marketing data environment in a structured, governed, and scalable way that supports both current reporting needs and future analytical capability Apply SCD, CDC, and DQ/DV frameworks rigorously across pipeline development ensuring that data arriving in the marketing master dataset is accurate, complete, historically traceable, and fit for the analytical and insight purposes it is intended to serve Evaluate and implement new technical solutions, data engineering patterns, and platform capabilities that improve the reliability, performance, and sophistication of BCG's marketing data infrastructure contributing MVPs and proofs of concept that demonstrate feasibility before committing to full implementation Data Quality, Governance & Security Own the data quality and governance standards for BCG's marketing data engineering environment implementing the monitoring, validation, and alerting frameworks that catch data quality issues before they surface as errors in stakeholder-facing dashboards or analytical outputs Implement data performance and data security policies that align with BCG's governance objectives, regulatory requirements, and privacy obligations working in close partnership with enterprise data governance, IT security, and legal colleagues to ensure the marketing data environment meets the firm's standards across all dimensions Maintain clear, accessible documentation of data models, pipeline architecture, transformation logic, and engineering decisions building institutional knowledge that reduces key-person dependency and supports the chapter's resilience as it grows AI & Identity Resolution Architecture Design the end-to-end identity resolution architecture spanning CRM, marketing automation, web/behavioral data, campaign platforms, and third-party data sources Define the matching strategy: deterministic rules (exact matches on email, phone, CRM ID) vs. probabilistic matching (fuzzy name/address matching, behavioral signals), and when each applies Design the "golden record" / unified profile structure what fields it contains, how conflicting values are resolved, and which source system wins for each data type Build a confidence-scoring framework so matches are tiered (auto-merge, flag-for-review, reject) rather than treated as all-or-nothing Define the survivorship rules most recent, most complete, most trusted source that determine what data persists into the unified profile when records merge Design for scale and extensibility so new data sources (new martech tools, new regions, new business lines) can be onboarded without re-architecting the core model Technical Monitoring & Incident Management Actively monitor the health, performance, and reliability of BCG's marketing data pipelines and Snowflake environment — establishing the observability frameworks, alerting standards, and incident response protocols that minimize disruption to the analytical products and insight outputs the marketing organization depends on Lead the triage and resolution of critical technical incidents with urgency, clarity, and sound engineering judgment — communicating clearly with product owners and stakeholders throughout, and ensuring that root cause analysis and remediation are completed systematically rather than reactively Identify and address performance bottlenecks across the data engineering environment — conducting regular performance reviews and implementing optimization improvements that keep the platform scalable and responsive as data volumes, analytical complexity, and user demand grow Cross-Functional & Stakeholder Partnership Build strong working relationships with external stakeholders across BCG's global data and technology organization ensuring that marketing's data engineering work is aligned with firm-wide data standards and that dependencies are managed proactively Partner with IT architecture and platform teams on shared infrastructure decisions — including AWS cloud services, Azure Active Directory integration, and CI/CD pipeline tooling — ensuring marketing's engineering choices are compatible with BCG's broader technology environment Engage with product portfolio management and cross-functional data product teams across finance, HR, legal, and other BCG functions — contributing a marketing analytics perspective to firm-wide data platform conversations and maintaining awareness of cross-functional data and security trends that affect the marketing data environment YOU'RE GOOD AT Leading a chapter of data engineers with technical authority and genuine investment in their development — you set a high bar, model it yourself, and bring people along rather than simply holding them to it Designing data pipeline architectures and Snowflake data models that are not just technically correct but genuinely built for the analytical consumption patterns of a sophisticated marketing analytics function — you think about the downstream insight need as much as the upstream engineering requirement Writing advanced SQL and well-structured dbt models that your colleagues can read, understand, maintain, and build on — you treat code quality and documentation as professional obligations, not optional extras Navigating the intersection of data engineering and marketing analytics with enough domain fluency to engage credibly with product owners, analysts, and insight leaders — you understand what they are trying to build and why, and you engineer solutions that serve those needs rather than just satisfying technical requirements Bringing a current and practical perspective on AI and its implications for data engineering — you are not evangelizing AI for its own sake, but you have a well-formed view of where intelligent automation, Snowflake Cortex, and LLM integration create genuine engineering opportunity in a marketing analytics context Staying calm and effective in critical incidents — you triage with sound judgment, communicate clearly under pressure, and resolve issues systematically rather than reactively Collaborating with product owners and Agile teams in a way that adds engineering value to product decisions — you show up to sprint ceremonies prepared, you flag technical risk early, and you help the squad make better product decisions by making the engineering trade-offs visible and understandable

8–10 years of data engineering experience with a strong focus on data warehouse architecture, pipeline development, and data modeling, including at least 2–3 years in a chapter lead, technical lead, or senior engineering leadership role Demonstrably advanced SQL proficiency and deep hands-on experience with Snowflake — including data modeling, performance optimization, security configuration, and consumption layer design for analytical workloads Expert-level proficiency with dbt for data transformation and data model development, and strong hands-on experience with Apache Airflow for pipeline orchestration and job scheduling Solid experience applying SCD, CDC, and DQ/DV frameworks in production data engineering environments — you have built these patterns, maintained them, and debugged them when they break Demonstrated ability to write clean, well-documented, version-controlled code — you use GitHub or Bitbucket as a professional standard, not an afterthought Experience integrating data from complex, multi-platform marketing or enterprise technology ecosystems — familiarity with platforms such as Dynamics CRM, Adobe Analytics, Marketo, Sprinklr, or equivalent marketing technology is a meaningful advantage Working knowledge of AI and machine learning concepts as they apply to data engineering — including intelligent pipeline orchestration, AI-assisted data quality, and the evolving role of Snowflake Cortex or equivalent capabilities in analytics environments Strong Python scripting skills for pipeline development, automation, and data engineering tooling; experience with PowerShell or equivalent a plus Experience with cloud platforms — AWS preferred, Azure and GCP also valued — and familiarity with CI/CD pipeline tooling and version control workflows in a production data engineering environment Experience working in Agile and scrum-based delivery environments — including active participation in sprint ceremonies, backlog grooming, and cross-functional squad collaboration with product owners, architects, and data SMEs Excellent written and verbal communication skills — including the ability to present architecture decisions, engineering trade-offs, and technical recommendations to non-technical product owners and marketing stakeholders clearly and confidently Experience with JIRA and Confluence for delivery management and technical documentation Familiarity with other data platforms including Oracle, SQL Server, or MDM systems is a plus Bachelor's degree in Computer Science, Information Science, Data Management, or a related field, or equivalent practical experience Who You'll Work With This role operates within BCG's Global Marketing analytics and data hub functions as the senior technical leader of the data engineering chapter that serves it. Your most important day-to-day working relationships are with the engineers in your chapter — the people whose technical growth, work quality, and professional development you are directly accountable for — and with the product owners across the marketing analytics and data hub squads whose roadmaps depend on the reliability and capability of the engineering infrastructure your chapter builds and maintains. Within the analytics function, you will partner closely with the Director of Marketing Analytics and the Director of Data Hub who run the squads who access, monitor, and deliver insights and data driven insights for the global marketing organization. You will also collaborate with the CRM data operations and CRM engineering leads — ensuring that the data quality and governance standards that apply at the platform level are reflected in the CRM data environment that feeds the broader marketing analytics ecosystem. Beyond the marketing analytics and data hub functions, you will be expected to engage regularly with BCG's enterprise data organization to ensure marketing's engineering work is aligned with firm-wide data standards and that shared infrastructure decisions reflect marketing's needs. You will also work with IT architecture, cloud platform, and security colleagues on the infrastructure and governance dimensions of the marketing data environment. At the most senior level, you will engage with the Director of Marketing Analytics & Data and Director of Data Hub as a peer and strategic partner — contributing the engineering perspective that shapes how the function's data platform capability evolves, how AI and emerging technology are incorporated into the chapter's roadmap, and how BCG's marketing analytics and data infrastructure is positioned to support the organization's most ambitious data and insight ambitions. This is a role for a data engineering leader who finds genuine satisfaction in the combination of deep technical craft and organizational impact — who wants to build something that is not just technically excellent but genuinely indispensable to how a world-class marketing organization understands and acts on its data. Additional info At BCG, our people and relationships are at the heart of everything we do. We believe that in-person collaboration plays an important role in our culture, mentorship, and professional development. For this role, you will generally be expected to work from a BCG office or in person with clients on a regular basis (typically around 50% of working time), depending on business needs and in line with local policies and practices. We aim to provide a dynamic and collaborative environment that fosters connection and teamwork. Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E - Verify Employer. Click here for more information on E-Verify.