Senior Big Data Engineer - Real-Time Pipelines

Sapient Corporation; Chicago (IL); On-site; USD 135,000 - 165,000; Full time

Job summary

Publicis Sapient is seeking a Senior Associate Data Engineering L2 to design, build, and maintain scalable Big Data solutions. You’ll work with large datasets and real-time processing, leveraging Hadoop, Spark, Kafka, and Flink across cloud platforms to enable data-driven decisions for clients.

You’ll implement ETL, data modeling, and data warehousing while ensuring data quality, security, and compliance. Collaboration with data scientists and business stakeholders is essential to deliver

Qualifications

• 5+ years of experience in Big Data engineering, data processing, and analytics.
• Proficiency with Hadoop, Spark, Kafka, Flink, and Hive.
• Experience with AWS, GCP, or Azure cloud platforms.
• Proficiency in Java, Scala, or Python for data processing.
• Hands-on with ETL, data modeling, and data warehousing.
• Knowledge of data governance, security, and compliance.

Responsibilities

• Design, develop, and maintain scalable Big Data pipelines.
• Support analytics, reporting, and ML applications with data workflows.
• Optimize storage, retrieval, and processing for performance.
• Collaborate with data scientists and stakeholders to meet data needs.
• Ensure data quality, security, and compliance.
• Automate data workflows and monitoring for reliability.
• Stay updated on emerging Big Data technologies.

Skills

Big Data

Spark

Kafka

Flink

Hive

Cloud platforms

Java/Python/Scala

ETL/Data warehousing

Data governance

SQL/NoSQL

Tools

Docker

Kubernetes

Job description

Publicis Sapient is seeking a Senior Associate Data Engineering L2 to design, build, and maintain scalable Big Data solutions. You’ll work with large datasets and real-time processing, leveraging Hadoop, Spark, Kafka, and Flink across cloud platforms to enable data-driven decisions for clients.

You’ll implement ETL, data modeling, and data warehousing while ensuring data quality, security, and compliance. Collaboration with data scientists and business stakeholders is essential to deliver