Data & AI Engineer: Build Scalable Data Pipelines

Deloitte France; United States; Hybrid; USD 84,000 - 141,000; Full time

Job summary

Deloitte is seeking a Data Engineer II to design, build, and optimize scalable data pipelines and data models that drive analytics and decision-making. You will collaborate with cross-functional teams to deliver reliable data solutions across cloud platforms and on-premises environments.

The role emphasizes data quality, production monitoring, and the ability to work in a fast-paced, client-facing environment with strong communication and problem-solving skills.

Qualifications

• Bachelor's degree in a quantitative field or related STEM discipline.
• 3+ years designing, building, and maintaining data pipelines and ETL/ELT workflows.
• 1+ years using Python and SQL for data analysis and production ETL.

Responsibilities

• Design, build, test, and maintain scalable data pipelines and workflows for ingesting, transforming, and delivering structured and unstructured data
• Develop and optimize data models, integration patterns, and storage solutions to support analytics, reporting, and operational use cases
• Collaborate with cross-functional stakeholders to define data requirements, troubleshoot issues, and implement data quality controls
• Build and support batch and near-real-time processing solutions using cloud-based and distributed data technologies
• Document technical designs, data lineage, and deployment processes, and support testing, release, and production stabilization activities

Skills

Team collaboration

Communication skills

Detail-oriented

Relationship building

Project leadership

Multitasking

Interpersonal skills

Deadline oriented

Guidance to others

Education

Bachelor's degree in a quantitative field

Master's degree preferred

Tools

Python

SQL

Job description

Deloitte is seeking a Data Engineer II to design, build, and optimize scalable data pipelines and data models that drive analytics and decision-making. You will collaborate with cross-functional teams to deliver reliable data solutions across cloud platforms and on-premises environments.

The role emphasizes data quality, production monitoring, and the ability to work in a fast-paced, client-facing environment with strong communication and problem-solving skills.