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

Role overview

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

This role also carries direct responsibility for aligning the marketing data layer with BCG's wider enterprise data approach.

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.

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.

Responsibilities

• 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.
• Build monitoring and alerting for match-rate quality, pipeline failures, and unexpected shifts in merge/split volume .
• 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.
• 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.
• 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.
• Design the end-to-end identity resolution architecture spanning CRM, marketing automation, web/behavioral data, campaign platforms, and third-party data sources.
• 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.
• 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.
• You will also work with IT architecture, cloud platform, and security colleagues on the infrastructure and governance dimensions of the marketing data environment.

Required qualifications

• 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 .

Preferred qualifications and skills

• 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 .

Employment details

• Location: Gurgaon [Haryana] [India]

Application details

• 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 .
• 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.

About the employer

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

Additional role details

• 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.
• 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.
• Chapter Leadership & Data Engineering Development.
• 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.
• 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.
• 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.
• AI & Identity Resolution Architecture.
• 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.
• Technical Monitoring & Incident Management.
• 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.
• 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.
• 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.
• Staying calm and effective in critical incidents — you triage with sound judgment, communicate clearly under pressure, and resolve issues systematically rather than reactively.
• 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 .
• Strong Python scripting skills for pipeline development, automation, and data engineering tooling; experience with PowerShell or equivalent a plus .
• 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 .
• 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.
• 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.
• 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.
• Data Quality, Governance & Security.