Senior Data Engineer — Cloud Pipelines, Hybrid, ML-Ready

HRCUS RAPP Illinois Inc; United States; Hybrid; USD 110,000 - 120,000; Full time

Benefits offered by this job

Health insurance

Stock options

401(k)

Paid time off

Job summary

RAPP is seeking a Senior Data Engineer to design, build, and scale cloud-native data pipelines and platforms. You will use Python, Airflow, AWS Lambda, DynamoDB, and dbt to enable advanced analytics, reporting, and ML use cases. Collaboration with creative teams and strong attention to detail are essential.

The role emphasizes scalable asset workflows, data governance, and cross-functional teamwork to improve efficiency and scalability in data operations.

Qualifications

• 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 DevOps practices.
• Strong problem-solving and communication skills.

Responsibilities

• Design, build, and maintain robust ETL/ELT pipelines using Python and Airflow.
• Develop serverless workflows leveraging AWS Lambda for scalable data processing.
• Implement and optimize dbt models for analytics and transformations.
• Data Architecture & Storage Design: 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 & Leadership: Partner with analytics, product, and engineering teams to deliver reliable datasets.
• Mentor junior engineers and enforce best practices in data engineering.

Skills

Python

Airflow

AWS Lambda

DynamoDB

dbt

Cloud AWS

ETL/ELT pipelines

Data modeling

CI/CD

Git

DevOps

Communication

Tools

Docker

Kubernetes

Git

CI/CD

Job description

RAPP is seeking a Senior Data Engineer to design, build, and scale cloud-native data pipelines and platforms. You will use Python, Airflow, AWS Lambda, DynamoDB, and dbt to enable advanced analytics, reporting, and ML use cases. Collaboration with creative teams and strong attention to detail are essential.

The role emphasizes scalable asset workflows, data governance, and cross-functional teamwork to improve efficiency and scalability in data operations.