Data Engineer II

ADT•Irving, TX

13d

About The Position

As a Data Engineer II on the AI Automation & Data team, you will serve as a senior data engineer responsible for designing, building, and optimizing complex data solutions that power ADT’s Enterprise Data Warehouse and AI initiatives. This role requires deep expertise in data engineering, strong architectural understanding, and the ability to lead, mentor, and influence engineering direction across multiple domains. You will work closely with architects, domain owners, and engineering teams (onshore and offshore) to deliver scalable, high‑quality data solutions that support ADT’s enterprise-wide data needs.

Requirements

Bachelor’s or master’s degree in computer science, engineering, or a related field.
Minimum of 12 years of experience in data engineering or a closely related field.
Expert-level proficiency in building and maintaining enterprise ETL pipelines.
Deep understanding of data warehousing concepts, including data architecture, dimensional modeling, and enterprise data design patterns.
Advanced SQL skills with extensive experience designing stored procedures, extracts, and analytical queries.
Hands-on experience with Python for scripting and data processing; strong expertise is not required.
Expertise with Informatica Cloud or similar ETL technologies.
Strong understanding of master data management and Type I & Type II table design.
Experience with cloud platforms, preferably GCP, or similar platforms.
Strong communication skills with the ability to influence engineering decisions across teams.
Demonstrated ability to lead, mentor, and provide technical direction to junior and mid-level engineers.
Proven ability to take ownership, drive delivery, and operate effectively in a fast-paced, multi-domain enterprise environment.

Nice To Haves

Experience with AI/ML tools (such as Vertex AI) is a plus.

Responsibilities

Architect, design, and build highly scalable and reliable ETL pipelines using Informatica Cloud, stored procedures, and other enterprise-grade tools.
Apply expert-level data warehousing knowledge to design efficient data models, manage Type I & Type II data structures, and ensure strong alignment with broader data architecture principles.
Develop advanced SQL solutions primarily for building complex stored procedures, generating extracts, and conducting in-depth data analysis.
Guide junior and mid-level engineers through mentorship, best practices, and thorough code reviews.
Coordinate daily with offshore engineering teams to ensure alignment, quality delivery, and seamless handoff of work.
Step up to own and lead critical components of the data engineering build when required, ensuring timely and high-quality execution.
Take on lead engineer responsibilities when needed, including technical decision-making, task delegation, and guiding development workflows.
Drive initiatives to enhance data engineering processes, monitor pipeline performance, and identify opportunities for optimization and efficiency gains.
Collaborate with teams using AI technologies (e.g., Vertex AI, ML APIs) to support model development, feature engineering, or data preparation activities.
Engage and influence stakeholders across various departments to understand business needs and align data solutions to drive business outcomes effectively.
Assist Data Architects in translating conceptual and logical designs into scalable, performant physical implementations.
Collaborate daily with Architects, Domain Owners, and Scrum Leads, influence solution direction from an engineering perspective.
Utilize Python for scripting and data processing tasks as needed (working proficiency; not required to be expert-level).
Ensure data accuracy, availability, and completeness across all solutions delivered to the enterprise.
Contribute to cloud-based solution design and implementation, preferably on Google Cloud Platform or similar platforms.
Troubleshoot and resolve complex data pipeline and infrastructure issues with minimal guidance.