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Accenture · 3 weeks ago

Marketing Data Analysis Manager - Financial Services

New York, One Manhattan West, Corp

Full-time

Onsite

Senior Level

$94K/yr - $294K/yr

7+ years exp

Accenture is a leading global professional services company that helps organizations build their digital core and enhance citizen services. The Marketing Data Analysis Manager will direct a team to evaluate marketing use cases and ensure optimal data assets are leveraged to deliver business value.

Business Information SystemsConstructionConsultingInformation ServicesInformation TechnologyInfrastructureManagement ConsultingOutsourcing

No H1B

Responsibilities

Lead Use Case Assessment

Lead the assessment of priority marketing use cases, collaborating with stakeholders to document findings, expected outcomes, and define impact

Analyze data needs, feasibility, and potential impact for each use case

Quantify the incremental value and business impact that each additional use case could deliver

Data Review, Source Identification & Requirements

Oversee detailed assessments of existing data strategies and architectures related to priority use cases

Identify, validate, and document the most relevant data sources (internal and external) for each use case

Evaluate the breadth and depth of data captured and ingested, ensuring completeness and relevance for business objectives

Partner with data product owners to understand where current data exists, what can be re-purposed for use cases, identify data gaps, and document the nuances and challenges for specific data sets

Metrics & Baseline Assessment

Establish the current state of key performance and success metrics for existing and proposed use cases

Analyze metric definitions, calculation methodologies, and data lineage to ensure accuracy and consistency

Identify gaps in data capture, metric coverage, and reporting capabilities

Stakeholder Engagement & Partnership

Conduct stakeholder interviews, build rapport, ask questions rooted in data domain experience (primarily marketing data, but other data sources like Nielsen, sales, panel, survey, etc.)

Partner with business, marketing, and technical stakeholders to elicit requirements and clarify objectives

Translate findings into clear, actionable documentation, including requirements, user stories and acceptance criteria for technical teams

Present insights and recommendations to both technical and non-technical audiences, including senior leadership

Data Quality, Governance & Best Practices

Champion data quality standards, governance principles, and taxonomy management across all assessment activities

Partner and collaborate with engineering lead and data modeling lead to ensure findings translate to development requirements and approach

Business & Commercial Analytics

Analyze and interpret commercial performance data (e.g., volumetrics, ATL revenue, distribution, product mix) to identify trends and growth opportunities

Translate commercial and consumer insights into actionable business recommendations

Media & Marketing Analytics

Evaluate media performance across traditional and digital sources, including impressions, GRPs/TRPs, cost-to-client, and channel-level performance

Work with digital media account data (Meta, TikTok, Snapchat, etc.) to derive and aggregate awareness, engagement, and conversion metrics

Consumer & Brand Insights

Process and parse consumer survey data, ensuring sound handling of survey structures, questions, and response scales

Build and interpret brand equity and consumption models, deriving meaningful KPIs for brand tracking and strategy

Qualification

Data Analysis & InterpretationMarketing AcumenTechnical ProficiencyGovernance & ComplianceCommunication & StorytellingBusiness & Commercial AnalyticsMedia & Marketing AnalyticsConsumer & Brand InsightsLeadership & CollaborationAgile PracticesStakeholder Management

Required

7+ years of experience in data analytics, specifically marketing, consumer, and digital domains with extensive expertise in data discovery, profiling, and assessment methodologies

Strong proficiency in identifying, integrating, and validating diverse data sources

Expertise in baselining and benchmarking key metrics, identify gaps, and recommend improvements

Excellent communication and stakeholder management skills

Experience gathering and documenting requirements

Knowledge of data governance, taxonomy, and quality standards

Familiarity with high-level data engineering concepts: data lake, data tables, metrics, dimension

Exposure to Agile and Product Management practices (backlog management, sprint planning, iterative delivery)

4+ years of experience in the Financial Services industry