Apply on Employer Site

Accenture · 2 weeks ago

Marketing Data Analysis Consultant - Products

New York, NY

Full-time

Onsite

Mid Level

$64K/yr - $206K/yr

3+ years exp

Accenture is a global professional services company that provides a range of services and solutions in strategy, consulting, digital, technology, and operations. The Marketing Data Analysis Consultant will be responsible for conducting comprehensive reviews of current data approaches and evaluating new marketing use cases, leveraging marketing data expertise to refine priorities and drive incremental value.

Business Information SystemsConstructionConsultingInformation ServicesInformation TechnologyInfrastructureManagement ConsultingOutsourcing

No H1B

Responsibilities

Assess priority marketing use cases, collaborating with stakeholders to document findings, define requirements and expected outcomes

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

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

Identify, validate, and document the 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

Link data requirements to discussions 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

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

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

Advocate for and apply data quality standards, governance principles, and taxonomy management across all assessment activities

Collaborate with engineering and product teams to ensure robust data pipelines and semantic data layers

Support the design and implementation of cloud-based data solutions (Azure preferred)

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

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

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

Marketing data analyticsData discovery methodologiesData governance standardsCloud-based data solutionsAgile practicesUser stories documentationStakeholder engagementData quality advocacyConsumer insights analysisBrand equity modeling

Required

3+ years of experience in marketing data analytics, campaign measurement, and attribution, as well as experience with consumer and digital data domains. This experience should include: Expertise in data discovery and assessment methodologies

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

Ability to baseline and benchmark key metrics, identify gaps, and recommend improvements

Experience documenting requirements and writing user stories for analytics and data products

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)

1+ year of experience supporting Product clients (Retail, Consumer Goods, Travel, Industrials)