Company Description
A division of Publicis Groupe, Publicis Digital Experience is a network of top-tier agencies designed to develop capabilities and solutions to enable growth and provide scaled access to the digital capabilities of Publicis Groupe in service of our clients. Together, the Publicis Digital Experience portfolio endeavors to create value at the intersection of technology and experiences to connect brands and people.
Our model to transform every brand experience will help clients navigate, develop, and activate commerce in a way that will provide them with a future-proof model for modern marketing. With our unique expertise in consumer engagement, CRM, and commerce, Publicis Digital Experience powers brands and empowers people in a new era of creativity. An ever-changing landscape and the need for fluid thinking is just part of our problem-solving nature. Which means we're untethered from any specific medium or method—we go where ideas will work best.
We are an expanding network of more than 7,000 employees across global offices, unified under the Publicis Digital Experience umbrella. Our portfolio includes agency brands such as Razorfish, Digitas, Mars United Commerce, Arc Worldwide, Saatchi \& Saatchi X, Plowshare and 3Share. Our capabilities span the full customer journey—from creative and experience to Commerce and CRM—through specialized practices like ConnectedCRM and the Publicis Commerce.
Overview
Part of the overall Analytics Group, the Analytics Engineering team is responsible for data modeling automation and preparing data needed by the Data Science team for modeling and the Business Analytics team for data analysis. This will involve documenting the data cleaning and transformation processes, automating these processes, ensuring data governance practices are followed, and maintaining a data catalog. The team is also responsible for developing all PowerBI dashboards based on client needs or Data Science outputs.
Core Responsibilities: Data Integration, Data Cleaning, Data Transformation, Data Warehousing, Dashboarding, MLOps, Charts \& Visualizations, Reporting Automation, etc.
Primary Tools: Databricks, Azure Synapse, Power BI
Primary Responsibilities
As an Analytics Engineer, you play a crucial role in developing and maintaining the data infrastructure that supports our analytics engineering capabilities. You work closely with data scientists, analysts, strategic planners, and other disciplines to ensure data quality and accessibility and implement best practices for data governance and security. Specifically, the Analytics Engineer will:
Develop and maintain data pipelines and ETL processes.
Optimize data infrastructure for efficient data processing.
Ensure data quality and accessibility for data scientists and analysts.
Collaborate with cross-functional teams to address data needs and challenges.
Implement data governance and security best practices.
Support annual planning initiatives with clients.
Work closely with cross-functional teams, including analysts, product managers and domain experts to understand business requirements, formulate problem statements, and deliver relevant data science solutions.
Develop and optimize machine learning models by processing, analyzing and extracting data from varying internal and external data sources.
Develop supervised, unsupervised, and semi-supervised machine learning models using state-of-the-art techniques to solve client problems.
Show up - be accountable, take responsibility, and get back up when you are down.
Make stuff.
Share so others can see what’s happening.
Skillsets Required
A bachelor’s/master’s degree in data analytics, computer science, or a directly related field.
3-5 years of industry experience in a data analytics or related role.
Proficiency in SQL for data querying and manipulation.
Experience with data warehousing solutions.
Design, implement, and manage ETL workflows to ensure data is accurately and efficiently collected, transformed, and loaded into our data warehouse.
Proficiency in programming languages such as Python and R.
Experience with cloud platforms such as AWS, Azure, and Google Cloud.
Experience in developing and deploying machine learning models.
Knowledge of machine learning engineering practices, including model versioning, deployment, and monitoring.
Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
Ability to design and develop scalable data pipelines for batch and real-time data processing.
Experience with big data technologies such as Apache Spark, Hadoop, or similar.
Proficiency in working with structured and unstructured data sources.
Knowledge of data governance and security best practices.
Strong understanding of data modeling techniques and best practices.
Experience with DevOps or MLOps practices for continuous integration and deployment.
Establish and create scalable and intuitive reporting methodologies through Power BI, suggesting the best representation and visualizations.
Identify business intelligence needs recommending the best KPIs and customer valuation models and dashboards.
Interpret data, analyze results, and identify trends or patterns in complex data sets.
Filter and “clean” data and review computer reports, printouts, and performance indicators to locate and correct data corruption problems.
Data collection, setting and leveraging DMP and CDP-based infrastructures, attribution modeling, A/B \& multivariate testing, and dynamic creative.
Develop, evaluate, test, and maintain architectures and data solutions such as ETL Pipelines, Data Warehouses, Data Marts, etc.
Automate data pipelines and develop automation workflows.
Develop scalable and intuitive ETL \& ELT pipelines from a variety of marketing sources such as Salesforce, Adobe Analytics, etc.
Identify data sources and create data pipelines using shell scripts or Python scripts.
Create technical documentation.
Plan data analysis work and develop execution estimates, continuously improving the accuracy of the estimates.
Develop Single Customer View stitching 1P data from various data sources.
Additional Information
Our Publicis Groupe motto “Viva La Différence” means we’re better together, and we believe that our differences make us stronger. It means we honor and celebrate all identities, across all facets of intersectionality, and it underpins all that we do as an organization. We are focused on fostering belonging and creating equitable \& inclusive experiences for all talent.
Publicis Groupe provides robust and inclusive benefit programs and policies to support the evolving and diverse needs of our talent and enable every person to grow and thrive. Our benefits package includes medical coverage, dental, vision, disability, 401K, as well as parental and family care leave, family forming assistance, tuition reimbursement, and flexible time off.
If you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com. All your information will be kept confidential according to EEO guidelines.
Compensation Range: - $75,000- $90,000 annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be January 30, 2026.