Summary
The GEICO Data Engineering team is seeking an experienced Senior Staff Software Engineer to drive data architecture and engineering efforts. You have a passion for efficient data engineering that is founded on sound operational and analytical data models and robust data architecture. You understand holistically how data moves through an organization, including how it is originated, transformed, derived, and persisted to enable business analytics and machine learning models. You have a strong track record of building high-performance and resilient data-intensive applications, data warehouses and lakehouses. This role requires in-depth knowledge of data modeling and architecture, data pipelines, and data management.
Position Description
Our Senior Staff Software Engineer is a key member of the engineering staff working across the organization to innovate and leverage industry best practices for our data engineering efforts as we embark on our Data transformation journey. Our team thrives and succeeds in delivering high quality data platforms, products and services to our business partners in a hyper-growth environment where priorities shift quickly.
Position Responsibilities
As a Senior Staff Software Engineer, you will:
- Thrive on and have deep knowledge of conceptual and logical data models for various domains
- Create and maintain a conceptual data model for the enterprise
- Develop logical and physical data models that are optimized for accuracy, performance, and scalability
- Live and breathe entities, relationships, aggregates, and different schema types for various use cases
- Develop and drive adoption of metadata management strategy
- Engage with business and product to guide them and choose the right entities and datasets for their analytics and ML solutions
- Collaborate with business partners to establish and evolve enterprise and business domain data models and strategies
- Identify, manage, and leverage data assets across the enterprise understanding the cross-domain data opportunities
- Provide technical leadership to data engineering teams to ensure the delivery of high-performance and resilient data solutions
- Promote the use of data architecture, data governance, and data management best practices at enterprise and domain levels
- Drive automation of modeling best practices and compliance with conceptual enterprise data model
- Have in-depth experience in understanding, profiling and defining, and standardizing data for efficient processing and utilization
- Define data architectures for acquiring data and ingesting into the enterprise data warehouse/lakehouse; develop POCs and MVPs
- Develop and maintain semantic views that provide a business-friendly layer on top of the data lakehouse; ensure semantic views are aligned with business requirements and are easy to understand
- Lead design sessions and code reviews to elevate the quality of engineering across the organization
- Influence and build vision with product managers, team members, customers, and other engineering teams to solve complex problems for building enterprise class business applications
- Work collaboratively with data engineers, software engineers, and business intelligence teams to ensure seamless integration and data flow across the enterprise data lakehouse
Qualifications
- You are customer-centric, always keeping the customer's experience at the forefront of the conversation
- Ability to identify and communicate enterprise data challenges and develop strategies to address them
- Knowledge of data management practices, legal and regulatory frameworks that impact and shape enterprise data
- Ability to influence across enterprise data teams and leadership
- Expertise in modern data architecture and data modeling best practices
- Fluency and expertise in modern data stacks, e.g. Snowflake, Apache Iceberg, DBT, Delta Lake, Spark, Apache Flink, Cassandra, PostgreSQL etc.
- Experience with Kimball, Inmon, Data Vault modeling techniques
- Experience with at least one modern language such as Go, Python, Java, including object-oriented design
- Understanding of data warehouse concepts including data modeling and OLAP
- Strong working knowledge of SQL and the ability to write, debug and optimize SQL queries and ETL jobs
- Fluency in DevOps concepts, cloud architecture, and CI/CD frameworks
- In-depth knowledge of data structures and algorithms
- Understanding of monitoring and troubleshooting tools such as OpenTelemetry, Prometheus, Grafana, Splunk etc.
- Strong knowledge and understanding of cloud-based data services on Azure, AWS, or GCP
- Strong problem-solving, analysis and estimation skills
- Strong oral and written communication skills
Experience
- 10+ years of professional experience in data modeling and design, data software development, and developing with big data technologies
- 8+ years of experience with architecture and design
- 6+ years of experience in open-source frameworks
- 4+ years of experience with AWS, GCP, Azure, or another cloud service
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