Senior Associate Data Engineering (Public Sector)
As a Digital Business Transformation partner of choice at Publicis Sapient, we’ve spent nearly three decades utilizing the disruptive power of technology and ingenuity to help digitally enable our client's businesses in their pursuit of the 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 by designing the products and services their customers truly value. In the space between next and now is how. And we believe that how you seize that space is everything.
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As a Senior Cloud Data Engineer, you will be responsible for designing, building, and maintaining our cloud-based data infrastructure. Your expertise in Apache Spark (Scala), Apache Airflow, AWS Glue, Python, Kubernetes, and Oracle will be crucial in ensuring efficient data processing, storage, and retrieval. Additionally, knowledge of Data Lakehouse technologies like Apache Iceberg or Databricks will be a significant advantage, enabling you to further enhance our data management capabilities.
- Design, develop, and deploy robust data pipelines and workflows using Apache Spark (Scala) and Apache Airflow to support data processing and transformation activities.
- Implement ETL processes to extract, transform, and load data from diverse sources into data warehouses and data lakes.
- Leverage AWS Glue for automated data cataloging, schema discovery, and data preparation tasks.
- Utilize Python to create scalable and reusable code for data manipulation and data engineering tasks.
- Manage and optimize data storage and retrieval processes on AWS and other cloud platforms.
- Implement and maintain Kubernetes-based solutions for containerized data applications.
- Collaborate with developers, analysts, and other stakeholders to understand data requirements and ensure data availability and quality.
- Monitor, troubleshoot, and optimize the performance of data pipelines and workflows.
- Ensure data security and privacy standards are met by following industry best practices and company policies.
- Stay updated with the latest trends and advancements in cloud data engineering and Data Lakehouse technologies, proposing suitable improvements and upgrades.
- Bachelor’s degree in computer science, Data Engineering, or a related field (or equivalent work experience).
- At least 3 years of hands-on experience working with Apache Spark (Scala) for data processing and analysis.
- Must be a U.S. Citizen or U.S. Permanent Resident
- Eligible for U.S. Government Clearance.
- Proficiency in Apache Airflow for building and orchestrating complex data workflows.
- Strong expertise in ETL (Extract, Transform, Load) processes and best practices.
- Advanced programming skills in Python for data engineering tasks and automation.
- In-depth understanding of cloud technologies and experience working with AWS services.
- Familiarity with Kubernetes for container orchestration and managing data applications in containers.
- Experience working with Oracle databases for data storage and retrieval needs.
- Knowledge of Data Lakehouse technologies like Apache Iceberg or Databricks is a strong plus.
- Strong problem-solving abilities and a proactive approach to identifying and resolving issues.
- Ability to work collaboratively in a team environment and communicate effectively with technical and non-technical stakeholders.
- Detail-oriented with a focus on delivering high-quality and scalable data solutions.
Annual Pay Range: 95,000 - 143,000 USD
The range shown represents a grouping of relevant ranges currently in use at Publicis Sapient. The actual range for this position may differ, depending on location and the specific skillset required for the work.
Benefits of Working Here:
- Flexible vacation policy
- Unlimited PTO's
- 16 company paid holidays annually
- Work Your World program
- Generous parental leave and new parent transition program
- Tuition reimbursement
- Corporate gift matching program