Job Description
**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**
As a **Senior Data Engineer** , you will be responsible for designing, developing, and maintaining scalable Big Data solutions.
You will work with large datasets, real-time processing frameworks, and cloud-based platforms to ensure clean, reliable, and actionable data for decision-making.
**Responsibilities**
**Your Impact**
+ Design, develop, and maintain large-scale data pipelines using Scala, Apache Spark, and SQL on AWS.
+ Reverse engineer SQL queries and Scala code to understand functionality, validate performance, and ensure maintainability.
+ Clean and prepare data by removing corrupted files, fixing coding errors, and handling data quality issues.
+ Review reports and performance indicators to identify and correct code or pipeline inefficiencies.
+ Create and maintain database designs, data models, and techniques for data mining and segmentation.
+ Identify, analyze, and interpret patterns and trends in complex datasets to support diagnosis, forecasting, and strategic decisions.
+ Implement data processing workflows leveraging AWS services such as EMR, Glue, Kinesis, Lambda, S3, and Redshift.
+ Collaborate with data scientists, analysts, engineers, and business stakeholders to translate requirements into reliable solutions.
+ Automate workflows, monitoring, and alerting processes to improve operational efficiency and reliability.
+ Prepare clear reports for management highlighting trends, patterns, and predictions using relevant data.
+ Ensure data quality, security, and compliance with AWS best practices and industry standards.
**Qualifications**
**Your Skills & Experience**
+ 5+ years of experience in Data Engineering with strong focus on Scala, Apache Spark, and SQL.
+ Previous exposure to streaming processing projects.
+ Proven experience reverse engineering SQL queries and Scala code to optimize performance and understand existing systems.
+ Strong knowledge of database design, data modeling, and data mining techniques.
+ Solid hands-on experience cleaning and preparing data, fixing coding errors, and ensuring high-quality datasets.
+ Experience designing and implementing ETL/data pipelines on AWS (e.g., EMR, Glue, Kinesis, Lambda, S3, Redshift).
+ Proficiency with statistical techniques to analyze datasets and validate insights.
+ Strong understanding of distributed computing, cloud storage, and performance optimization in large-scale systems.
**Set Yourself Apart With**
+ Knowledge of other programming languages like Python, R, Oracle, JavaScript, XML, or ETL frameworks.
+ Familiarity with data visualization tools (Tableau, Qlik).
+ Experience with reporting packages (Business Objects, etc.).
+ Familiarity with containerization and orchestration tools (Docker, Kubernetes) for deploying Big Data workloads.
+ Knowledge of data governance, security, and compliance frameworks.
+ AWS Certifications such as AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect.
**Additional information**
**This is a full time 100% Remote contractor agreement running through March 31st 2026, with high possibility of extension.**