Senior Data Engineer

Price Benowitz Accident Injury Lawyers, LLP

Senior Data Engineer building scalable ETL pipelines and BigQuery data warehouses for Price Benowitz LLP, a technology-enabled law firm. Automating cloud data workflows on GCP for analytics, reporting, and operational efficiency.

Posted 8/8/2026full-timeRemote • Washington • 🇺🇸 United StatesSenior💰 $16 - $18 per hourWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing scalable ETL/ELT data pipelines using Python and SQL, with a strong focus on optimizing data warehouse solutions in Google BigQuery and leveraging Google Cloud Platform services for efficient data processing.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyGoogle BigQuery ExpertiseData Pipeline DevelopmentGCP Data Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL DevelopmentData WarehousingData ModelingData TransformationPerformance OptimizationREST API IntegrationTerraformCI/CD PracticesData SecurityData Quality Monitoring

Soft Skills

Analytical SkillsProblem-SolvingCommunicationCross-Functional Collaboration

Tools & Technologies

Google Cloud PlatformBigQueryCloud RunCloud SchedulerCloud WorkflowsPub/SubCloud TasksCloud BatchGitGitHub

Industry Keywords

Data EngineeringETLELTCloud Data PlatformsInfrastructure as Code

Tech Stack

Tools & technologies

BigQueryCloudETLGoogle Cloud PlatformPythonSQLTerraform

About the role

Key responsibilities & impact

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 for performance, reliability, scalability, and cost efficiency
Develop and maintain data processing solutions on Google Cloud Platform
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 Run, Cloud Scheduler, Cloud Workflows, Pub/Sub, Cloud Tasks, and Cloud Batch for scalable data architectures

Requirements

What you’ll need

5+ years of experience in data engineering, ETL/ELT, and cloud data platforms
Strong proficiency in Python and SQL
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
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, B2 or higher
Resume and cover letter must be submitted in English

Benefits

Comp & perks

Remote work
Monday through Friday, 9:00 AM–6:00 PM Eastern Time
Equal opportunity employer
Inclusive work environment
Diversity commitment