Data Engineer - Manager/Specialist

Company description

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' businesses through designing the products and services their customers truly value.

Overview

You will lead a team and create technology products that help people have the best experience they have ever had. We are looking for a leader with a strong passion for both technology and people, who is motivated to build outstanding products. The ideal candidate brings deep technical expertise across multiple technologies, a strong track record of delivery, and proven experience in building and leading high-performance engineering teams.

Responsibilities

• Design, implement, and test data pipelines, ETL/ELT processes, and data storage solutions
• Build and maintain scalable, reliable, and high-performance pipelines for structured and unstructured data
• Work with big data technologies and distributed systems to process and transform large datasets
• Collaborate with data modelers, data scientists, and solution architects to ensure efficient data flows and optimal storage
• Partner with data scientists and analysts to deliver clean, well-structured, and accessible data
• Coordinate with integration teams and data source owners for smooth ingestion of data from multiple systems
• Automate provisioning, deployments, and environment management for data platforms
• Create and support APIs and data services for internal and external consumers
• Ensure solutions meet requirements for scalability, performance, data quality, and governance

Qualifications

• Hands-on experience with ETL/ELT design and implementation
• Familiarity with big data ecosystems (e.g., Spark, Hadoop, Kafka, Flink)
• Experience with one or more cloud platforms (Azure, AWS, GCP) and modern data engineering tools (e.g., Databricks, Snowflake, BigQuery, Synapse)
• Proficiency in programming languages such as Python, Java
• Solid understanding of SQL and experience with both relational and non-relational databases
• Experience with data modeling, schema design, and data partitioning strategies
• Knowledge of workflow orchestration tools (e.g., Airflow, Data Factory) is a plus