AI Data Engineer: Build Production-Grade Azure Pipelines

ManpowerGroup; Redmond; On-site; AUD 152,000 - 160,000; Full time

Benefits offered by this job

Medical Plan

Dental Plan

Vision Plan

Health Savings Account

Health Flexible Spending Account

Dependent Care Flexible Spending Allow

401(k) with match

Weekly Pay

Job summary

ManpowerGroup | AI Data Engineer role in Redmond, WA, onsite. You will build and optimize Python pipelines for data ingestion, OCR processing, and dataset preparation to support confidential model development. The role focuses on scalable data engineering, automated quality checks, and Azure storage synchronization.

The ideal candidate has 5+ years in data-related roles, strong Python expertise, and hands-on experience with large datasets and Azure data services.

Qualifications

• Five+ years of data-focused work with hands-on dataset building.
• Strong Python skills for module development, debugging and testing.
• Experience processing large structured and unstructured data efficiently.

Responsibilities

• Develop, maintain, and optimize Python pipelines for data ingestion and processing.
• Run large-scale batch jobs, monitor failures, and ensure reliable retries.
• Create automated quality checks for data integrity and completeness.
• Prepare training-ready datasets through filtering, tokenization, and formatting.
• Manage bulk transfers and synchronization with Azure storage.

Skills

Data engineering

Python

Large datasets processing

Tools

Azure Blob Storage

Azure Data Lake Storage

SQL

Git

Linux

Pandas

NumPy

JSON/JSONL

CSV

Parquet

Job description

ManpowerGroup | AI Data Engineer role in Redmond, WA, onsite. You will build and optimize Python pipelines for data ingestion, OCR processing, and dataset preparation to support confidential model development. The role focuses on scalable data engineering, automated quality checks, and Azure storage synchronization.

The ideal candidate has 5+ years in data-related roles, strong Python expertise, and hands-on experience with large datasets and Azure data services.