Data Engineer

Company Description Frontdoor, Inc. is on a mission to make home ownership simple by transforming the home services industry with innovative, customer-focused solutions. Backed by more than 50 years of expertise as the nation’s largest provider of home service plans, the company serves over two million customers across the U.S. and responds to millions of service requests each year. Frontdoor operates a family of brands—including American Home Shield, HSA, Landmark, and OneGuard—through a large network of pre-qualified contractor firms and technicians. Team members join a culture that emphasizes ownership, accountability, problem solving, and continuous innovation to improve customer experiences. The leadership team brings deep experience in disrupting industries, building digital platforms, and delivering world-class service, creating an environment where people are encouraged to do great work every day.
Summary: The Data Engineer L4 will bring a mindset of automation and innovation to the table. In addition to sharp technical skills, this person must be a strong communicator and collaborator who can partner up with business stakeholders to understand their needs and solve their data problems. As a data engineer at Frontdoor, you will be working in a fast-paced environment and using cutting-edge cloud technologies to develop a scalable data platform that will support years of company growth.
Responsibilities:
Build and maintain highly complex scalable data pipelines for both batch and stream processing in a cloud-computing environment.
Apply highly complex dimensional modeling to design tables and views that map business processes into an enterprise data model.
Optimize database architecture by trading off storage and computation to achieve low cost and high performance.
Build and support highly complex ETL infrastructure to deliver clean and reliable data to the organization.
Develop new products and services via ingestion, processing, and formatting data for reporting and analytics.
Interact face-to-face with business stakeholders, develop cooperative relationships, and acquire domain knowledge of the business.
Proactively automate manual processes throughout the business for higher efficiency, robustness, and speed.
Enforce production standards and governance best practices in the management of enterprise-level data, metrics, and reports.
Manage small to medium projects.
May include other duties as assigned.
Minimum Experience required: 5+ years of experience in relevant field
Required Skills:
Excellent communication and inter-personal skills.
Versatile and quick learner with ability to pick up any new skills necessary to get the job done.
Demonstrated strength in data modeling, ETL development, data warehousing, data pipeline and data lake creation.
Extensive experience with cloud infrastructure and tools for AWS and GCP.
Demonstrable proficiency in Python development and advanced SQL querying.
Strong grasp of business elements and ability to convert requirements into database models and full-data pipeline systems.
Experience with visualization and reporting tools, such as Looker and Tableau.
Experience with cloud data warehouses such as Snowflake
Experience building data lakes in the cloud
Preferred Skills:
Full stack experience, including microservice and web app development.
Knowledge of big data platforms, such as Hadoop and Spark.

Work arrangement
No