Publicis Sapient : Director, Data Engineering

Brief Description of position:


Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally-enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting and customer experience with agile engineering and problem-solving creativity. As digital pioneers with 20,000 people and 53 offices around the globe, our experience spanning technology, data sciences, consulting and customer obsession – combined with our culture of curiosity and relentlessness – enables us to accelerate our clients’ businesses through designing the products and services their customers truly value. Publicis Sapient is the digital business transformation hub of Publicis Groupe. For more information, visit

We at Publicis Sapient, enable our clients to thrive in Next and to create business value through expert strategies, customer-centric experience design, and world-class product engineering.

The future of business is disruptive, transformative and becoming digital to the core.

In our 20+ years in IT, never before have we seen such a dire need for transformation in every major industry - from financial services to automotive, consumer products, retail, energy, and travel.

To make this transformative journey a reality in these exciting times, we seek thought leaders and rock stars who will: 

  • brave it out to go do the next; “what will be” from “what is”
  • exhibit the optimism that says there is no limit to what we can achieve 
  • deeply-skilled, bold, collaborative, flexible
  • Reimagine the way the world works to help businesses improve the daily lives of people and the world. 

Our people thrive because of the belief that it is both our privilege and responsibility to usher our clients and the world into Next.

Our work is fueled by 

  • challenging boundaries, 
  • multidisciplinary collaboration, 
  • highly agile teams, and 
  • the power of the newest technologies and platforms.

If that’s you, come talk to us!

This is the world-class engineering team where you should build your career.

Job Summary: 

As Director in Data Engineering, you will be responsible for 

  • Data assessments and data audits 
  • Defining and executing data strategy for clients. 
  • High quality strategy, definition and delivery of solutions
  • Technical Architecture, Design and Delivery of Big Data and Cloud Data solutions 
  • Data Governance & Security 
  • Distribution Computation Frameworks, Performance Optimizations
  • Analytics & Visualizations
  • Infrastructure & Cloud Computing
  • Data Management Platforms

The role requires a hands-on technologist with expertise in Big Data, Cloud, Batch and Streaming based data solutions provide strategic and tactical direction to team and customers especially in the areas of marketing and technology. The person should have a strong programming background like Java/Scala/Python along with Spark and other related computing frameworks.

As data engineering practitioner, you should have a point of view and understanding of build vs. buy, performance considerations, hosting, business intelligence, reporting & analytics. Ideally, you have experience in integrating data with marketing scenarios like segmentation, targeting, consumer 360 view, etc.

Role & Responsibilities:

  1. Provide inputs to define and execute strategic roadmap for enterprise and big data architecture by identifying the current landscape and future business goals
  2. Provide technical leadership and hands-on implementation role in the areas of Big data techniques including data ingestion, data transformation/processing, data quality, data modeling, data visualization involving end to end life cycle using agile/scrum implementation approach. 
  3. Technical lead a globally distributed team to deliver high quality solutions. Manage functional & non-functional scope, quality and timelines. 
  4. Functional and technical understanding related to data-driven digital marketing & customer experience analytics, insights and decision making solution i.e. Customer Behavior, Customer Engagement, Customer 360 view, Customer Data Platform (CDP), Data Management Platforms (DMPs) and Customer Relationship Management (CRM). 
  5. Help establish standard data practices and frameworks like data governance, data quality, data validation, data security, data privacy, scheduling, monitoring and logging/error management. 
  6. Help establish best practice like standards and guidelines for design & development, deployment, support of Big data / cloud solutions and platforms analytics. 
  7. Help establish best practice in acquiring, storing and analyzing structured, semi-structured and un-structured data from the enterprise and outside like social
  8. Come up with Big Data and Analytics solutions based on the business goals and appropriate data visualization to support the goals
  9. Manage and provide technical leadership to large data programs or multiple programs implementation based on the requirement using agile technologies
  10. Run workshops with clients and align client stakeholders to optimal solutions
  11. Should exhibit and demonstrate Thought Leadership and provide business and technical consulting to the clients and mentorship/coaching to the team members. 


Experience Guidelines: 

Mandatory Experience and Competencies: 




Overall 15 years of IT experience with 8+ years in Data related technologies


5+ years of experience in Big Data technologies and expertise in 1+ years in cloud related data services (AWS / Azure / GCP) 


Have led data audits / assessment, defining data strategy and provide consulting skills to the clients. 


Have led technical Architecture, Design and Delivery of Big Data and Cloud Data solutions (AWS, Azure, GCP) 


Setup best design patterns, coding practices, code review process, automation and quality guidelines and processes. 


Expert in data ingestion, distributed data processing (batch and streaming) and programming languages preferably in Java/Scala and/or Python as secondary language.


Lead proposals (RFPs) from solution, architecture, estimation and framework standpoint


End to end architecture including Analytics, ML and Activation tools in overall Data-driven Digital Business Transformation (DBT) and Marketing Transformation programs


Should have experience in NoSQL databases (Cassandra/HBase/MongoDB) and in which use cases to use which one. 


Good understanding of Data Governance, Data Security Data Cataloging and Data Lineage concepts and any tools experience in these areas like Collibra is preferred. 


Good understanding of Continuous Integration and Continuous Delivery (CI/CD) using Cloud based DevOps services or Jenkins/Bamboo, Maven, Junit, SonarQube, Terraform (one-click infrastructure setup) 


Should exhibit thought leadership in the areas i.e. writing blogs, creating PoVs, industry trends, attending/presenting in internal/external technical forums, mentorship etc. 


Excellent communication, presentation and collaboration skills 


Lead / participate in Data CoE initiatives e.g. building accelerators, knowledge sharing sessions, coaching/mentoring team members 

Preferred Experience and Knowledge:





Knowledge of Storm / Flink / Kafka streaming 


Containers, Dockers and Kubernetes Engine 


Distributed Messaging Queues ((RabbitMQ, ActiveMQ) 


Data Security (Kerberos / Sentry / Ranger) 


One or more traditional ETL tools experience (Informatica, Talend etc.)


Search/Indexing Technologies (Solr) 


Knowledge of Machine Learning 


Agile ways of working (Scrum / Kanban) 


Master’s / Bachelor’s Degree in Computer Engineering, Computer Science, or a related field.

Minimum Qualification:

We use cookies essential for this site to function well. Please click to help us improve its usefulness with additional cookies. Learn about our use of cookies in our Privacy Policy.


We believe in making Analytics Vidhya the best experience possible for Data Science enthusiasts. Help us by providing valuable Feedback.