Senior Data Engineer

Domino's•Ann Arbor, MI

22h

About The Position

As a Senior Data Engineer, you will operate as a technical expert responsible for designing, building, and scaling enterprise-grade data engineering solutions across our cloud-native data platform on Azure and Databricks. This role requires deep technical knowledge, strong engineering judgment, and the ability to deliver high-impact solutions that support analytics, AI/ML, operational reporting, and streaming data solutions. You will partner closely with Data Architects, Platform Admins, Cloud Engineers, Product Owners, and cross-functional stakeholders to translate strategy and architecture into production-grade high-quality solutions. You will lead complex technical work within your domain, mentor engineers, raise engineering standards, and influence delivery across multiple products, platforms, and business capabilities.

Requirements

8+ years of experience in data engineering, including experience delivering complex, enterprise-scale data solutions; Azure experience preferred.
Advanced technical expertise in Cloud based data warehouses (Databricks Preferred), Spark, Delta Lake, Azure Services, data integration, data modeling, and performance optimization.
Proven experience in building and optimizing large-scale ETL/ELT pipelines and data lakehouse architectures.
Solid understanding of data lakehouse modeling, data warehousing, and performance tuning.
Experience with Infrastructure as Code (Terraform, ARM templates) and DevOps tools (Git, Azure DevOps, Jenkins).
Familiarity with RBAC, data security, and compliance frameworks.
Strong communication and collaboration skills, with the ability to influence technical direction, clarify tradeoffs, and align engineering decisions across teams and stakeholders.
Experience with Agile methodologies and working in cross-functional product teams.
Demonstrated ability to lead through influence, mentor engineers, manage technical ambiguity, and drive outcomes across a broad scope of products, platforms, and stakeholders.

Nice To Haves

Experience with Customer 360 data products, identity resolution, customer profile enrichment, and activation use cases is highly desired.
Experience designing and supporting streaming data solutions is highly desired, including Kafka or similar event streaming platforms.
Martech exposure is preferred, including experience supporting marketing, personalization, campaign, loyalty, or customer engagement data use cases.

Responsibilities

Apply advanced technical knowledge to design, build, and optimize scalable data pipelines, reusable engineering frameworks, and platform capabilities using Azure Data Factory, Databricks, Spark, streaming and related cloud-native technologies.
Lead engineering design and implementation for ingestion, transformation, and data product frameworks that support structured, semi-structured, and unstructured data at enterprise scale.
Implement automation for data ingestion, processing, validation, and monitoring to ensure reliability and observability.
Drive implementation of future-state data architecture and cloud migration patterns, ensuring solutions are reliable, secure, maintainable, and aligned to enterprise modernization goals.
Optimize data workflows for performance and cost, leveraging Delta Lake, partitioning, caching, and compute scaling strategies.
Define data access controls and RBAC policies in collaboration with security and governance teams.
Provide technical leadership within the team by mentoring engineers, reviewing solution designs, setting engineering standards, and promoting best practices for CI/CD, testing, automation, observability, and cloud-native delivery.
Partner with AI/ML, analytics, and business teams to enable high-value real-time and batch data activation use cases that improve decision-making and business outcomes.
Ensure compliance with data governance, privacy, and security standards.