Data Engineer

PUBLICIS GROUPE•Arlington, VA

38d

About The Position

As a Senior Data Engineer L1, you will be responsible for designing, developing, and maintaining scalable data platforms that enable data-driven decision-making. You will work with cross-functional teams to build and optimize data pipelines, ensuring high performance, reliability, and security of enterprise data solutions.

Requirements

5+ years of experience in data engineering, data platforms, or related fields.
Strong expertise in data processing frameworks such as Apache Spark, Apache Flink, or cloud-based data services (AWS Glue, Azure Data Factory, Google Cloud Dataflow).
Proficiency in SQL, NoSQL databases, and data warehousing solutions (Snowflake, Redshift, BigQuery, etc.).
Experience with data modeling, ETL/ELT processes, and data integration techniques.
Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.
Strong programming skills in Python, Scala, or Java for data processing and automation.
Knowledge of data security, governance, and compliance frameworks.
Experience with real-time data processing, streaming analytics, and event-driven architectures is a plus.
Strong problem-solving and analytical skills with a focus on performance optimization and scalability.

Nice To Haves

Must be eligible for government clearance
Certifications in cloud platforms (AWS Certified Data Analytics - Specialty, Google Professional Data Engineer, or Azure Data Engineer Associate).
Experience with containerization and orchestration tools (Docker, Kubernetes).
Knowledge of data lakes, data mesh, and modern data architecture principles.
Exposure to machine learning pipelines and AI-driven data processing.

Responsibilities

Design, develop, and maintain data platforms to support business intelligence, analytics, and machine learning initiatives.
Build and optimize data pipelines, ensuring efficient data processing, storage, and retrieval.
Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver scalable solutions.
Implement data governance, security, and compliance best practices to ensure data integrity and regulatory adherence.
Automate data workflows using tools like Apache Spark, Apache Flink, or cloud-based data processing services.
Optimize data storage and retrieval mechanisms for performance and cost efficiency.
Troubleshoot and resolve data platform issues, ensuring minimal downtime and maximum availability.
Stay updated with emerging data technologies and best practices to drive continuous improvement.