Manager Data Engineering
3 weeks ago
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. 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's businesses through designing the products and services their customers truly value.
OverviewAs a Manager, Data Engineering at Publicis Sapient, you will guide clients through complex data challenges, architecting and implementing innovative solutions that drive digital transformation.
If you're passionate about solving complex data challenges, shaping digital transformation strategies, and working in a collaborative, growth-focused environment, we'd love to hear from you
ResponsibilitiesYour expertise will shape large-scale data ingestion, processing, storage, and analytics in mostly cloud environments. You will lead discussions on key Data Engineering topics such as data models, data storage, performance optimization, security, DevOps, and test automation.
This role requires a hands-on approach, working collaboratively with other Data specialists in a culture that values continuous learning and knowledge sharing. You will take a leading role in driving the growth of our Data Engineering capability to successfully advise clients on improving their Data Architecture to support future ambitions.
You will work closely with clients across industries, helping them navigate their digital transformation journeys by delivering scalable, high-quality data solutions.
Qualifications- Experience in Data Engineering with strong knowledge of Data Architecture
- Solid understanding of cloud architecture, demonstrated with Microsoft Azure.
- Proficient in designing, developing, and maintaining data pipelines
- Preferably knowledge of Azure data technologies including Azure Data Factory (ADF), Synapse, and Databricks/ Spark Pools.
- Prior extensive experience with Python, SQL
- Strong knowledge of scalable data models and optimization techniques (e.g., bucketing, sharding, indexing).
- Experience in DevOps practices for data solutions, including automated testing and CI/CD pipelines.
- Deep understanding of database technologies, including relational and NoSQL databases
- Experience with big data ingestion tools and distributed messaging frameworks
- Expertise in distributed data processing frameworks
- Excellent problem-solving, analytical, and communication skills, with the ability to engage with clients and stakeholders.
Set Yourself Apart With
- Experience or exposure to ML/AI engineering
- Experience with containerization and associated microservice tooling such as Docker, and Kubernetes.
- Knowledge of data security (authentication, authorization, encryption for data at rest and in transit).
- Understanding of monitoring and alerting tools for data environments.
- Exposure to data governance, cataloging, and lineage tools.
- Cloud or data technology certifications.
- Active participation in the Data Engineering community (blogs, keynotes, POCs, hackathons).
- Experience or exposure to working with Software or Platform engineering teams
- A Bachelor's or Master's degree in Computer Engineering, Computer Science, or a related field.
Benefits of Working Here
- Hybrid working model and flexible working hours.
- Strong people first company culture.
- Numerous learning opportunities to support your professional growth.
- Amazing opportunities for career progression.
- Staff incentives and rewards schemes.
- Company pension plan and occupational disability insurance.
- Discounts on travel, culture, and leisure activities.
- "Work Your World Program" – every Publicis Sapient employee is entitled to work anywhere in the world for up to 6 weeks every year.
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