Senior Data Engineer

Rocket Companies•Detroit, MI

1d•Hybrid

About The Position

As a Senior Data Engineer, you'll engage in the design, development, and maintenance of data platforms and solutions. This includes applying data management principles to pipelines and delivering analytical and operational solutions to enable data-driven decision-making and data activation use cases. You’ll design and develop data ingestion and transformation solutions, working across a hybrid data environment to build scalable products and services that meet business needs. As a senior member of the team, you’ll also mentor and support the growth of your teammates while helping drive best practices across the data engineering lifecycle.

Requirements

7 years of experience building data solutions, including relational and non-relational databases and batch/real-time data pipelines using cloud services
5 years of experience with dimensional or tabular data modeling
Experience designing and developing complex data transformation pipelines
5 years of experience with CI/CD and automated deployments
Expertise writing complex queries (SQL/NoSQL)
Expertise in performance tuning, debugging, and troubleshooting data processing jobs, including ETLs
5 years of experience in Python development, including AWS Lambda functions
Proficiency in a functional or object-oriented programming language
Strong understanding of database and server internals
Knowledge of Linux system administration, shell scripting, and basic networking
Experience developing and consuming REST APIs

Nice To Haves

Degree (or equivalent experience) in computer science, information technology, or a related field
Knowledge of disaster recovery and backup strategies for data systems
Experience mentoring and developing other engineers

Responsibilities

Develop ETL and ELT processes to source and curate data from various enterprise systems, ensuring speed and quality of delivery
Develop tabular and dimensional data models to support analytical and operational use cases
Build and maintain data processing jobs to refresh data on a regular cadence
Guide the identification, investigation, and resolution of data quality issues, ensuring data is secure and reliable
Utilize advanced debugging techniques to troubleshoot complex data pipeline and processing issues
Lead code review sessions with a focus on performance, scalability, and maintainability
Work in a hybrid data environment spanning on-premises and cloud data platforms
Develop relational and non-relational data models to meet user and business needs
Proactively identify upstream and downstream dependencies that may impact pipeline performance or reliability
Monitor and address performance and scalability issues across large-scale data platforms
Participate in on-call rotations for incident management and production support
Mentor team members and contribute to their technical development
Partner with leadership to identify and address technical debt and improve team processes
Stay current on industry trends and promote adoption of best practices across the team
Contribute to engineering community initiatives to increase visibility into data engineering work