Note: The job is a remote job and is open to candidates in USA. Price Benowitz, LLP is a mid-sized law firm headquartered in Washington, D.C., focused on leveraging technology to improve efficiency and enhance client service. They are seeking a Sr. Data Engineer to design and develop scalable data solutions and optimize cloud data workflows to support their Technology & Data team.
Responsibilities
- Design and develop scalable ETL/ELT data pipelines using Python and SQL
- Build and optimize data warehouse solutions in Google BigQuery, including partitioning, clustering, and query tuning
- Develop automated data ingestion and transformation pipelines integrating REST APIs and external data sources
- Design data models supporting analytics, business intelligence, and reporting
- Optimize cloud data workflows to improve performance, reliability, scalability, and cost efficiency
- Develop and maintain data processing solutions on Google Cloud Platform (GCP)
- Automate scheduled data pipelines, data refreshes, and reporting processes
- Integrate GCP services including BigQuery, Secret Manager, and Google Workspace APIs
- Implement secure authentication and authorization using service accounts and IAM best practices
- Develop reusable, modular, and maintainable ETL frameworks
- Collaborate with cross-functional teams to deliver reliable and scalable data solutions
- Use Git and GitHub for version control and collaborative development
- Apply Terraform and GitHub Actions to support Infrastructure as Code and CI/CD practices
- Leverage cloud-native services such as Cloud Run, Cloud Scheduler, Cloud Workflows, Pub/Sub, Cloud Tasks, and Cloud Batch to support scalable data architectures
Skills
- 5+ years of experience in data engineering, ETL/ELT, and cloud data platforms
- Strong proficiency in Python and SQL, with hands-on experience developing data pipelines and transformation workflows
- Strong experience with Google BigQuery, including data warehousing, data modeling, partitioning, clustering, and performance optimization
- Hands-on experience with GCP and cloud-native data engineering solutions
- Experience integrating REST APIs and external data sources into data platforms
- Familiarity with Cloud Run, Cloud Scheduler, Cloud Workflows, Pub/Sub, Cloud Tasks, and Cloud Batch for scalable and automated cloud-native architectures
- Experience with Terraform, Git, GitHub, and CI/CD practices, preferably using GitHub Actions
- Understanding of IAM, service accounts, data security, data quality, monitoring, and pipeline reliability
- Strong analytical, problem-solving, communication, and cross-functional collaboration skills
- Strong Professional English proficiency is required (B2 or higher), as all internal communication, documentation, meetings, and collaboration are conducted in English
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