Data Engineer

• Build and maintain Python backend services, APIs, and asynchronous workflows in production
• Design and optimize ETL pipelines, scheduled jobs, and complex BigQuery queries on large historical and real estate datasets covering 30,000+ ZIP codes
• Manage Google Cloud Platform services including Compute Engine, BigQuery, Cloud Storage, Pub/Sub, monitoring, and load balancing
• Precompute, package, compress, and cache data to efficiently serve high-traffic applications
• Make frontend adjustments in React, Next.js, and TypeScript using AI assistants to connect backend APIs to the UI
• Own features end-to-end from data ingestion and ETL processing through BigQuery, APIs, and frontend delivery
• Monitor production features to evaluate user adoption and performance using PostHog product analytics

Senior Backend Developer, Python, Data Engineering, GCP

• Own data workflows end to end, including ingestion, storage, orchestration, transformation, validation, and delivery
• Build and maintain inbound and outbound data transfers using cloud storage, secure file transfer protocols, and other integration methods
• Develop and maintain ETL and ELT pipelines using workflow orchestration and event-driven processing
• Manage data across cloud storage, data warehouses, and analytical databases
• Design and optimize data models, schemas, queries, and transformations
• Own custom datasets supporting large clients and company partnerships, including their sources, business definitions, lineage, and downstream dependencies
• Partner with Customer Success, Operations, and Engineering to clarify requirements, investigate discrepancies, and communicate technical constraints and data behavior
• Implement and maintain data quality checks, automated tests, monitoring, and alerts
• Troubleshoot production issues across transfers, pipelines, and databases; identify root causes and implement lasting fixes
• Maintain documentation covering data flows, dataset definitions, architectural decisions, and operational recovery procedures
• Evaluate technical approaches through research and prototypes, explaining tradeoffs in reliability, performance, cost, and maintainability
• Apply access controls and secure data handling practices throughout the data lifecycle

• Migrate, mirror, update, and maintain records between BodyShop Booster and external customer systems
• Review source data and ensure complete and accurate transfer to destination platforms
• Work with external management systems, reporting tools, and collision-industry platforms such as CCC ONE
• Maintain customer, vehicle, repair, appointment, and related operational information across multiple systems
• Reconcile data to identify missing, duplicated, inconsistent, or inaccurate records
• Investigate discrepancies and take corrective action
• Follow documented workflows and customer-specific requirements
• Handle PII and confidential customer information according to security and privacy requirements
• Document completed migrations, updates, exceptions, and unresolved issues
• Escalate system issues, unexpected data behavior, or workflow inconsistencies
• Meet turnaround-time expectations while maintaining high accuracy
• Assist with migration processes, documentation, checklists, and quality-control procedures
• Collaborate with Customer Experience, Support, Implementation, Product, and Engineering teams on data and integration issues

Data Migration Engineer

• Design, build, and optimize ETL/ELT workflows using SQL, Python, dbt, and Airflow
• Create and refine scalable data models primarily within BigQuery
• Cleanse, transform, and structure data for accurate analysis and reporting
• Mentor junior engineers and promote best practices in coding, data modeling, and system design
• Collaborate with data analysts and business stakeholders to translate business needs into technical requirements
• Create summary tables and enhance database models for Data Analysts
• Maintain documentation for data systems, pipelines, data flows, and schemas
• Deploy datasets, reports, and dashboards to Superset
• Apply software development best practices, including version control, testing, and modular code design
• Work within an agile development framework and contribute to continuous improvement
• Present completed data products and gather stakeholder feedback
• Own complex data problems from root-cause identification through production-ready solutions
• Conduct performance audits on data pipelines, databases, and dashboards and implement optimizations

Senior Data Engineer

• Definir, desarrollar y validar scripts y procesos técnicos para ejecutar la migración de datos punta a punta
• Implementar controles de calidad, mecanismos de integridad, trazabilidad y reconciliación para evitar pérdida o corrupción de datos
• Participar en la preparación técnica y brindar soporte operativo durante las ventanas de corte y migración
• Colaborar con equipos globales y asegurar la alineación con estándares técnicos internacionales
• Contribuir a la transformación de una plataforma de adquirencia legacy hacia una solución moderna de procesamiento de datos

Especialista Técnico de Migración de Datos – Bilingüe

• Create and configure GA4 properties across multiple sites and lines of business
• Define and deploy standard and custom events, triggers, and parameters using Google Tag Manager
• Execute real-time quality assurance for data collection
• Build and manage scalable Google Cloud data environments using BigQuery, Cloud Functions, and Pub/Sub
• Configure GA4-to-BigQuery exports and manage secure IAM and service account permissions
• Write LookML semantic models and develop standardized Looker dashboards
• Build and orchestrate ETL and reverse ETL pipelines using sources such as Iterable and GA4
• Establish identity resolution and audience syncing capabilities through CDP integrations
• Support SEO/GEO discoverability and experimentation initiatives
• Audit existing analytics setups and deliver end-to-end data ecosystems for global brands
• Introduce SQL standards, data modeling best practices, and pipeline orchestration frameworks
• Advise internal leadership and external clients and mentor data engineers

Google Cloud Data Engineer

• Diseñar, desarrollar y mantener pipelines de datos para integración, transformación y procesamiento de información
• Implementar y gestionar procesos de orquestación con Airflow y AWS Step Functions
• Diseñar e implementar soluciones sobre Data Lakes, Data Warehouses y Lakehouses
• Participar en el modelado de datos con enfoques dimensionales, de estrella y copo de nieve
• Desarrollar soluciones utilizando servicios y herramientas de AWS
• Participar en la implementación y despliegue mediante AWS CodePipeline y AWS CDK
• Colaborar en la definición y evolución de soluciones de datos con criterios de calidad, escalabilidad y mantenibilidad
• Investigar tecnologías para resolver desafíos técnicos y mejorar continuamente las soluciones
• Contribuir a la calidad, disponibilidad y evolución de los productos de datos

• Design, build, and maintain scalable production data pipelines
• Ingest, process, and transform large volumes of data from multiple sources
• Develop solutions for data standardization, normalization, matching, and validation
• Build data quality controls and monitoring to identify malformed, inconsistent, or incorrect data
• Design reliable approaches to data corrections, updates, reprocessing, and backfills
• Improve the architecture, scalability, reliability, and performance of the data platform
• Take end-to-end ownership of technical solutions and production quality
• Work closely with a small engineering team while independently driving the assigned area of responsibility
• Use AI-assisted engineering tools and practices to improve development efficiency