Senior Data Engineer
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Job Description
Senior Data Engineer designing and maintaining reliable data pipelines and scalable infrastructure for a personal injury law firm. Contributing to analytics, reporting, and decisions across the organization.
Responsibilities:
- Join a rapidly growing national firm at a formative stage
- Make a visible, measurable impact on a rapidly growing business
- Grow your skills, responsibility, and influence as the firm scales
- Work alongside high-caliber, mission-driven teammates who care deeply about doing great work
- Design, build, and maintain reliable data ingestion pipelines from internal systems and third-party data sources
- Implement scalable ELT workflows that process and deliver data across the organization
- Maintain transformation pipelines and ensure reliable delivery of analytics-ready datasets
- Manage and optimize the performance, reliability, and scalability of the company’s cloud data warehouse environment
- Maintain orchestration frameworks and scheduling systems that support data workflows
- Optimize data pipeline performance, compute utilization, and system efficiency
- Implement monitoring, alerting, and observability across data pipelines and platform components
- Ensure data freshness and system uptime meet defined service expectations
- Diagnose and resolve production issues including pipeline failures, data quality issues, and performance bottlenecks
- Maintain version-controlled data infrastructure and CI/CD workflows for data pipelines
- Implement testing and validation practices to ensure data quality and reliability
- Partner with the Director of Data to implement data architecture and platform improvements
- Support analytics and BI teams by ensuring reliable and well-modeled datasets are available for reporting and analysis
- Contribute engineering input to platform improvements and technical roadmap initiatives
Requirements:
- 5+ years of experience building and maintaining production data pipelines
- Strong SQL skills and experience working with large datasets
- Experience with modern cloud data warehouses such as Snowflake or BigQuery
- Experience building transformation workflows using dbt or similar tools
- Experience working with orchestration tools such as Airflow
- Strong understanding of data pipeline reliability, performance optimization, and scalability
- Experience using version control systems such as Git in collaborative development environments
- Nice to Have: Experience supporting data infrastructure used for machine learning workflows
- Experience building feature pipelines or supporting predictive modeling workloads
- Experience using Python for data processing and pipeline development
- Experience implementing monitoring and observability for data systems
- Experience working in high-growth or rapidly scaling environments
- Strong communication skills—written and verbal
- Ability to think critically, prioritize effectively, and execute with speed.
Benefits:
- Health insurance
- Expected to work flexible hours
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