Mercury InsuranceRemote
Sr Mgr Data Engineering
United States of America
Full Time
2 hours ago
$128,000 - $252,000 USD
No H1B
Key skills
PythonSQLGenAIOpenAIClaudeGeminiAnalyticsSnowflakeBigQueryRedshiftDatabricksKafkaAirflowdbtAWSAzureGCPGitSaaSCI/CDLeadershipMentoring
About this role
Mercury Insurance is seeking a highly experienced Sr. Manager to join their Data Service team. In this role, you will partner closely with the Engineering organization to implement data technology and optimize the technology stack while leading teams to deliver scalable, data-driven technology.
Responsibilities:
- Manage and guide data teams with hands-on experience to execute on enterprise data strategy
- Provide technical guidance for the team, raise the bar on the latest data technologies, and mentor data resources
- Design, develop, and implement end-to-end EDW data processing encompassing multiple Data Marts
- Build and manage scalable data pipelines to load EDW and data science environments
- Automate data operations to manage 100s of pipelines
- Automate data validation and testing of pipelines
- Collaborate with engineering teams to productionize data pipelines with high reliability and performance
Requirements:
- BS in Computer Science or Equivalent
- 5-10 years People Management Experience: experience managing, mentoring, and growing high-performing teams of data and analytics engineers
- Architectural Expertise: Proven experience redesigning foundational data pipelines and enterprise data models with the ability to make high-quality decisions regarding grain, entities, relationships, and slowly changing dimensions
- Strong Modeling Standards: Mastery of modern modeling patterns (3NF, dimensional, and Star/Snowflake) and the ability to guide teams toward structures that support real-world business processes and analytics
- Operational Excellence: A passion for data reliability, including the implementation of data quality frameworks, observability, and guardrails to reduce manual processes and technical debt
- Technical Skills: Expert-level proficiency in SQL, Python, and production experience with Informatica, DBT (models, tests, packages), along with familiarity with orchestration tools (Airflow, Tivoli, or Dagster)
- Modern Stack Experience: Hands-on experience with Lakehouse/Warehouse technologies (Redshift, Databricks, Snowflake, or BigQuery) and layered architecture (Bronze/Silver/Gold)
- Engineering Best Practices: A commitment to automation-first principles, using Git, CI/CD, and DRY patterns within a cloud environment (AWS/GCP/Azure)
- Data Leadership: A 'data product' mindset rather than a 'ticket' mindset, with the ability to translate business problems into requirements, prioritize roadmaps, and manage stakeholders
- Experience in leveraging GenAI/LLMs(OpenAI/Claude/Gemini) to solve time-consuming critical problems
- MS Preferred
- Data streaming(Kafka or similar) knowledge preferred
- Experience in an Insurance, SaaS, or marketplace environment is a plus