Senior Data Engineer; Cod: RN – AZ

We are looking for a Senior Data Engineer to join our Machine Learning team and build the data infrastructure that powers our AI and predictive systems. This role focuses on designing and maintaining scalable pipelines and data platforms that ensure machine learning models receive reliable, high-quality data in the right format and at the right time.

As a senior team member, you will work independently, contribute to technical decisions, and help guide junior engineers while collaborating closely with Machine Learning Engineers, Data Scientists, and Platform teams.

• Design, build, and maintain real-time and batch data pipelines for large-scale ML workloads.
• Implement streaming data solutions using Amazon Kinesis and Apache Flink
  .
• Own and maintain the Feature Store
  , ensuring consistency, reuse, and reliability of ML input data.
• Support and optimize data workflows powering ML models on Amazon Sage Maker
  .
• Organize, catalog, and transform datasets using AWS Glue
  .
• Ensure data quality, availability, and monitoring across the ML data lifecycle.
• Collaborate with ML Engineers and Data Scientists to deliver reliable datasets for experimentation and production models.
• Optimize data infrastructure for scalability, performance, and cost efficiency.
• Contribute to architectural decisions and mentor junior team members.

• 5+ years of experience in Data Engineering building production data pipelines and infrastructure.
• Hands‑on experience with real‑time streaming technologies such as Amazon Kinesis or Apache Flink
  .
• Proven experience managing or building a Feature Store for machine learning workflows.
• Production experience supporting ML platforms using Amazon Sage Maker
  .
• Strong experience with AWS Glue for data transformation and cataloging.
• Strong programming skills in Python or Scala
  , plus solid SQL knowledge.
• Familiarity with core AWS services such as S3
  , Athena
  , IAM
  , and related ecosystem tools.
• Strong problem‑solving and communication skills.

• Experience with workflow orchestration tools such as Apache Airflow or AWS Step Functions
  .
• Background in MLOps and supporting production ML systems.
• Experience designing data quality validation and observability frameworks.
• Exposure to large‑scale distributed data processing environments.

A successful candidate will demonstrate strong ownership, the ability to lead technical decisions, work with minimal supervision, and deliver scalable solutions in complex production environments. Seniority is reflected through impact, autonomy, and technical leadership rather than years of experience alone.

• Machine Learning Engineers building and deploying models
• Data Scientists designing experiments and analyzing results
• Platform and Infrastructure Engineers managing cloud environments

Strong collaboration and communication skills are essential for success in this role.

• Competitive compensation and benefits package.
• Opportunities for growth and professional development.
• Flexible work arrangements (remote or hybrid).
• Comprehensive leave policies, including PTO and holidays.
• Monthly connectivity allowance.

At Nybble Group
, we are dedicated to transforming businesses with the power of technology. For over 20 years, we have helped clients optimize operations and increase productivity through process automation, smart document processing, and advanced data analytics. We believe in fostering a collaborative and innovative culture where every team member can thrive.