In-Demand Snowflake data engineer Jobs

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- $130,000 - $160,000 a year
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Senior Analyst

Publicis Groupe Holdings B.V -
Pyrmont NSW

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Job Details

$130,000 - $160,000 a year
7 days ago

Qualifications

Data modelling
Azure
NoSQL
E-commerce
Databases
SQL
AWS
Natural language processing
AI
Analytics

Full Job Description

The transformation you will experience:

The Analytics Manager is accountable for discovering, assessing and presenting insights using Publicis proprietary data solutions and methodologies to help creative, CX and commerce teams decode brand and customer problems.

This role goes beyond reporting or isolated modelling. You will translate convoluted data into human-centered insights that inform creative ideas, experience design, and commercial outcomes — including for large-scale ecommerce organisation with convoluted customer journeys and data ecosystems.

You will work as part of EDGE’s central Analytics and AI capability, embedding into agency teams while contributing to shared, reusable solutions that scale across all Publicis clients.

Your scope will include:

Discover and interrogate insights using EDGE’s proprietary data solutions, connected identity assets, and advanced analytics methodologies.
Assess intricate, multi-source data to uncover behavioural, cultural, and commercial insights that inform brand, creative, CX, and commerce strategies.
Present insights clearly and compellingly to creative, strategy, and client teams — translating data into narratives that inspire action and ideas.
Help agencies and clients realise tangible value from data through better solution-making, creative effectiveness, and customer experience outcomes.
Work in close partnership with creative, strategy, media, and CX teams to embed insights directly into creative development and experience design.
Assist the development of creative and customer experience solutions for brand problems, including ecommerce optimisation, customer lifecycle growth, and connected journeys.
Act as a bridge between data and creativity, ensuring insights are actionable, relevant, and grounded in real customer behaviour.
Build and apply advanced analytics techniques to find a solution to real business and brand obstacles.
Contribute to analytics and AI solutions that move from discovery through to production, reuse, and ongoing optimisation.
Apply modern techniques such as predictive modelling, NLP, and retrieval-based analytics where appropriate, always aligned to governance and use-case value.
Collaborate closely with Data Engineers, Data Solutions Architects, and AI Product Managers to ensure analytics are scalable, production-ready, and efficient.
Leverage and evolve EDGE’s proprietary data products, methodologies, and frameworks to deliver differentiated insights for clients.
Contribute to shared analytics components and patterns that can be reused across agencies, clients, and engagements.
Help strengthen EDGE’s intellectual property by documenting approaches, insights frameworks, and learnings.
Stay current with emerging analytics, data, and AI techniques, with a focus on what can be applied safely and at scale.
Contribute to raising data and analytics fluency across agency teams through hands-on collaboration rather than standalone training.

What type of person will be successful in this role:

Advertising agency experience preferred
Proven experience in analytics, data science, or applied insights roles.
Strong foundations in statistics, analytics, and data modelling.
Hands-on experience with Python, SQL, and modern analytics environments.
Proven aptitude to translate convoluted data into clear, compelling insights for non-technical audiences.
Experience working with creative, CX, media, or strategy teams in an agency, consulting, or brand environment.
Experience and exposure to some advanced techniques such as GBM, NLP, and NoSQL databases.
Experience working with proprietary or first-party data assets, identity-based data, or convoluted customer datasets.
Exposure to ecommerce analytics, customer lifecycle assessment, or digital experience optimisation.
Familiarity with cloud platforms (e.g. AWS, Azure, Snowflake), modern data stacks, and production analytics workflows.
Experience contributing to reusable methodologies, frameworks, or analytics products.
Comfort working in fast-moving, multi-disciplinary teams where creativity and data intersect

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