Associate Data Engineer (AWS) - Big Data Pipelines

Sapient Corporation; Atlanta (GA); On-site; USD 91,000 - 119,000; Full time

Benefits offered by this job

Competitive compensation package

Health benefits

Generous paid leave

Job summary

Publicis Sapient in Atlanta, GA seeks an Associate Data Engineer to design, develop, and maintain scalable Big Data solutions. You will work with large datasets, real-time processing frameworks, and cloud-based data platforms to enable data-driven decision-making for clients.

Key responsibilities include building and optimizing data pipelines with Hadoop, Spark, Kafka, and Flink; implementing data processing and ETL workflows for analytics, reporting, and machine learning.

Qualifications

• 5+ years of experience in Big Data engineering and analytics.
• Proficient with Hadoop, Spark, Kafka, Flink, and Hive.
• Experience with AWS, GCP, or Azure.
• Proficient in Java, Scala, or Python for data processing.
• Hands-on with data modeling, ETL, and data warehousing.
• Strong understanding of distributed computing, streaming, and real-time processing.
• Experience with SQL, NoSQL, and data lakes; data governance basics.

Responsibilities

• Design, develop, and maintain Big Data pipelines and architectures.
• Build and optimize data processing workflows for analytics and ML.
• Improve data storage, retrieval, and processing performance.
• Collaborate with data scientists, analysts, and stakeholders to define data requirements.
• Ensure data quality, security, and regulatory compliance.
• Automate data workflows and monitoring to improve reliability.
• Stay current with emerging Big Data technologies and best practices.

Skills

Hadoop

Spark

Kafka

Flink

Hive

Java

Scala

Python

Data modeling

ETL

Data warehousing

SQL

NoSQL

Data lakes

Distributed computing

Cloud platforms

Tools

Docker

Kubernetes

Job description

Publicis Sapient in Atlanta, GA seeks an Associate Data Engineer to design, develop, and maintain scalable Big Data solutions. You will work with large datasets, real-time processing frameworks, and cloud-based data platforms to enable data-driven decision-making for clients.

Key responsibilities include building and optimizing data pipelines with Hadoop, Spark, Kafka, and Flink; implementing data processing and ETL workflows for analytics, reporting, and machine learning.