Início Arábia Saudita Senior Manager Data Engineering
Início Arábia Saudita Senior Manager Data Engineering
Senior Manager Data Engineering
Detalhes do emprego
Company description 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. Overview Publicis Sapient has an outstanding opportunity for a senior data leader to join our business and assume a key role within the Data Engineering capability. This role will see the successful individual lead the charge in enterprise scale data engineering transformation programmes for our global clients. In addition, they will help to grow and shape data practice at Publicis Sapient into a world-class capability. Responsibilities Your Impact:
- Deliver state-of-the-art data solutions for a range of clients in KSA.
- 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 practice through thought leadership, building accelerators and grooming/mentoring talent across PS.
- Extensive experience in Data technologies across streaming and batch-oriented realms and cutting across data acquisition, storage, processing, consumption patterns in operational and analytical domains, and expertise in cloud related data services (AWS / Azure / GCP).
- End to end data architecture skills including Analytics, ML and Activation tools in overall Data-driven Digital Business Transformation (DBT).
- Have led technical Architecture, Design and Delivery of Big Data and Cloud Data solutions (AWS, Azure, GCP) for multiple projects.
- Expert in distributed data processing frameworks like Spark, Storm, Flink across batch and streaming realms, programming languages preferably in Java/Scala and/or Python as secondary language and distributed messaging/streaming frameworks like Kafka, Pulsar, Google Pub/Sub, Azure EventHub, AWS Kinesis.
- 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.
- Experience with setting up data engineering practices across architecture, design, coding and quality assurance and deployment of such through industry-standard DevOps practices for CI/CD and leveraging tools like Jenkins/Bamboo, Maven, Junit, SonarQube, Terraform (one-click infrastructure setup), Kubernetes, containerization.
- Solid 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, driving mindshare through blogs, point of views, industry participation, coaching/mentoring team members, and keeping abreast through continuous learning.
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