Staff Data & AI Platform Engineer

Adusa; Quincy (MA); Hybrid; USD 136,000 - 204,000; Full time

Job summary

Ahold Delhaize USA is looking for a Staff Data & AI Platform Engineer to design reference architectures for data ingestion, transformation, and delivery. The role emphasizes automation, observability, and security across CI/CD pipelines, using Terraform/Ansible/CloudFormation, and will involve hybrid in-person and remote work with core days at Quincy, MA.

The ideal candidate has 10+ years in data engineering, strong Azure, Databricks, and Datadog experience, and a proven ability to lead data

Qualifications

• Bachelor's degree or equivalent years of work experience.
• 10+ years in data engineering with large scale systems.
• 10+ years working with Azure.
• 5+ years working with Databricks.
• 5+ years working with Datadog.
• Proficiency in distributed data processing, orchestration, and storage patterns.
• Strong automation/scripting skills and version control practices.
• Excellent cross team communication and influence.

Responsibilities

• Design reusable patterns for batch and streaming ingestion, transformations, and data product delivery, optimizing for performance and scale.
• Build automation for quality, lineage, and governance checks integrated into CI/CD, including deployment scripts and pipeline templates that reduce manual effort.
• Create and evolve internal tooling, developer platforms, and golden paths that improve reliability and time‑to‑delivery for data teams.
• Harden security and privacy controls (access, encryption, masking) across platforms and pipelines, integrating controls into automated delivery workflows.
• Elevate reliability with SLOs, telemetry, monitoring/logging/tracing, and automated rollback/reprocessing; contribute to observability implementations (e.g., DataDog).
• Integrate and optimize cloud services and container orchestration where relevant to improve scalability and reduce operational toil.
• Maintain infrastructure as code and repeatable environments using tools such as Terraform, Ansible, or CloudFormation.
• Guide solution decisions for complex programs; run technical reviews and threat/quality modeling to ensure robust outcomes.
• Document standards, playbooks, and reusable components to reduce rework and improve consistency across teams.
• Coach teams on data modeling, performance optimization, and design thinking for data consumer experience.

Skills

Data engineering

Automation scripting

Cross-team communication

Data governance

Education

Bachelor's degree or equivalent

Tools

Azure

Databricks

Datadog

Job description

Introduction

Ahold Delhaize USA, a division of global food retailer Ahold Delhaize, is part of the U.S. family of brands, which also includes five leading omnichannel grocery brands – Food Lion, Giant Food, The GIANT Company, Hannaford and Stop & Shop. Ahold Delhaize USA associates support the brands with a wide range of services, including Finance, Legal, Sustainability, Commercial, Digital and E-commerce, Technology and more.

Overview

The Staff Data & AI Platform Engineer operates as a senior technical authority who designs reference architectures and reusable patterns for data ingestion, transformation, storage, and delivery-embedding automation, observability, and security into every stage.

Our flexible/hybrid work schedule includes 3 in-person days at one of our core locations (Chicago, IL | Quincy, MA | Salisbury, NC | Mauldin, SC| Scarborough, ME) and 2 remote days.

Applicants must be currently authorized to work in the United States on a full‑time basis.

Responsibilities

• Design reusable patterns for batch and streaming ingestion, transformations, and data product delivery, optimizing for performance and scale.
• Build automation for quality, lineage, and governance checks integrated into CI/CD, including deployment scripts and pipeline templates that reduce manual effort.
• Create and evolve internal tooling, developer platforms, and golden paths that improve reliability and time‑to‑delivery for data teams.
• Harden security and privacy controls (access, encryption, masking) across platforms and pipelines, integrating controls into automated delivery workflows.
• Elevate reliability with SLOs, telemetry, monitoring/logging/tracing, and automated rollback/reprocessing; contribute to observability implementations (e.g., DataDog).
• Integrate and optimize cloud services and container orchestration where relevant to improve scalability and reduce operational toil.
• Maintain infrastructure as code and repeatable environments using tools such as Terraform, Ansible, or CloudFormation.
• Guide solution decisions for complex programs; run technical reviews and threat/quality modeling to ensure robust outcomes.
• Document standards, playbooks, and reusable components to reduce rework and improve consistency across teams.
• Coach teams on data modeling, performance optimization, and design thinking for data consumer experience.
• May be called upon to support critical escalations and must be available during urgent IT incidents as needed.

Requirements

• Bachelor's degree or equivalent years of work experience.
• 10+ years in data engineering with large scale systems.
• 10+ years working with Azure
• 5+ years working with Databricks
• 5+ years working with Datadog
• Proficiency in distributed data processing, orchestration, and storage patterns.
• Strong automation/scripting skills and version control practices.
• Excellent cross team communication and influence.

Preferred Qualifications

• Experience with feature stores and ML ready data patterns.
• Knowledge of cost optimization and workload right sizing.

Salary Range: $136,160.00-$204,240.00

Actual compensation offered to a candidate may vary based on their unique qualifications and experience, internal equity, and market conditions. Final compensation decisions will be made in accordance with company policies and applicable laws.