Director, Data Engineering - #16619
Publicis Sapient is a digital transformation partner helping established organisations 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. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value.
What will you do?
- Deliver state-of-the-art data solutions for a range of financial services clients across the retail, commercial, investment, and challenger bank sectors.
- Lead PS transformation in superior engineering approach towards data
- Help to develop state-of-the-art solutions that unlock the value of clients’ data for their organization together with AI, machine learning, and analytics teams
- Bring tried and tested consulting skills honed in client-facing roles
- Engage with business and technology stakeholders all the way to C-Level, appropriately increasing/decreasing the level of detail for your audience
- Provide and develop data thought leadership across PS
The role requires a hands-on technologist with expertise in Big Data, Cloud, Batch and Streaming based data solutions, providing strategic and tactical direction to teams and customers especially in the areas of marketing and technology. The individual should have a strong programming background in technologies like Java/Scala/Python along with Spark and other related computing frameworks.
As a data engineering practitioner, you will also have a strong point of view on and understanding of build vs. buy, performance considerations, hosting, business intelligence and reporting & analytics. Ideally, you will also have experience in integrating data with marketing scenarios like segmentation, targeting, consumer 360 view etc.
- Extensive experience in Big Data technologies and expertise in cloud related data services (AWS / Azure / GCP)
- Have led technical Architecture, Design and Delivery of Big Data and Cloud Data solutions (AWS, Azure, GCP) for multiple projects
- 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, distributed messaging and ingestion frameworks (Kafka, Pulsar, Pub/Sub etc)
- End to end architecture including Analytics, ML and Activation tools in overall Data-driven Digital Business Transformation (DBT) and Marketing Transformation programs
- Experience with NoSQL databases (Cassandra/HBase/MongoDB/ElasticSearch/Neo4j) and scalable analytical data stores like Snowflake, BigQuery, Redshift, Teradata
- Knowledge of scalable data models that address a wide variety of consumption patterns including random-access, sequential access including necessary optimizations like bucketing, aggregating, sharding.
- Experience of Performance tuning, optimisation, and scaling solutions from a storage/processing standpoint
- 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), Kubernetes, containerization, optimisation
- Good understanding of Data Governance, Data Security, Data Cataloguing and Data Lineage concepts (any tools experience in these areas like Collibra is preferred)
- Have led data audits / assessment, defining data strategy and provide consulting skills to the clients
- Lead proposals (RFPs) from solution, architecture, estimation, and framework standpoint
- Exhibit thought leadership in Data Engineering e.g. writing blogs, creating PoV’s, possess knowledge of 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
Benefits of Working Here:
- Fully paid annual leave of 22 working days
- Free private health insurance extended to employee and direct dependents
- Return air ticket to home country per year to employee and direct dependents
- Schooling allowance offered based on the policy