Senior Data Engineer

Agency:

RAPP

Job Function:

Data and Analytics

Job Subfunction:

Data Engineering

Job Description:

WHO WE ARE:

We are RAPP – world leaders in activating growth with precision and empathy  a global, next-generation precision marketing agency we leverage data, creativity, technology, and empathy to foster client growth. We champion individuality in the marketing solutions we create, and in our workplace. We fight for solutions that adapt to the individual’s needs, beliefs, behaviors, and aspirations.

We foster an inclusive workplace that emphasizes personal well-being.

HOW WE DO IT:

At RAPP, our fearless superconnectors help to create value from personal brand experiences by focusing on three key areas: connected data, connected content and connected decisioning.

Our data analysts identify who that person is, our strategists understand what they want, and our award-winning technologists and creatives know how to deliver it – ensuring we’re able to activate authentic customer connections for our clients.

Part of Omnicom’s Precision Marketing Group, RAPP is comprised of 2,000+ creatives, technologists, strategists, and data and marketing scientists across 15+ global markets.

YOUR ROLE:

We are looking for a Senior Data Engineer with deep expertise in building scalable, cloud-native data pipelines and platforms. The ideal candidate is highly skilled in Python, Apache Airflow, AWS Lambda, DynamoDB, and dbt , and has experience designing reliable data workflows that enable advanced analytics, reporting, and machine learning use cases. The ideal candidate will have strong attention to detail, a passion for information management, and the ability to work collaboratively with creative teams to enhance the efficiency and scalability of our asset workflows.

YOUR RESPONSIBILITIES:

Data Pipeline Development

• Design, build, and maintain robust ETL/ELT pipelines using Python and Airflow
  .
• Develop serverless workflows leveraging AWS Lambda for scalable event-driven data processing.
• Implement and optimize dbt models for analytics and transformations.

Data Architecture & Storage

• Design schemas and manage data in DynamoDB and other cloud-native storage solutions.
• Ensure high availability, scalability, and performance of data systems.
• Integrate structured, semi-structured, and unstructured data sources.

Automation & Orchestration

• Build workflow orchestration strategies using Airflow for scheduling and monitoring pipelines.
• Automate infrastructure deployment and CI/CD pipelines for data services.

Quality & Governance

• Implement data validation, testing, and monitoring frameworks.
• Ensure compliance with security, privacy, and governance standards.

Collaboration & Leadershi

• Partner with analytics, product, and engineering teams to deliver reliable datasets.
• Mentor junior engineers and enforce best practices in data engineering.
• Actively contribute to improving team efficiency, scalability, and standards.

REQUIRED SKILLS:

• 5–8+ years of experience in data engineering, software engineering, or a related role.
• Strong expertise in Python for data engineering and automation.
• Hands-on experience with Apache Airflow for orchestration.
• Proficiency with AWS Lambda and serverless design patterns.
• Solid experience with DynamoDB (schema design, performance tuning, scaling).
• Strong knowledge of dbt for transformation and analytics modeling.
• Experience with cloud environments (AWS preferred).
• Familiarity with CI/CD workflows, Git, and Dev Ops practices.
• Strong problem solving and communication skills.

Preferred Qualifications

• Experience with other AWS services (S3, Glue, Redshift, Kinesis).
• Familiarity with data warehouse and data lake architectures.
• Exposure to real-time streaming and event-driven data pipelines.
• Knowledge of containerization (Docker, Kubernetes).

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