Senior Data Engineer (GCP & Data Integration)

Applaudo Studios

About The Position

We are seeking a hands-on Senior Data Engineer who enjoys building reliable, scalable data pipelines and integrations across cloud environments. The ideal candidate is comfortable working across different layers of the data ecosystem, from API integrations and transformation logic to cloud-based pipelines and warehouse validation, and possesses the technical depth to troubleshoot issues across the full data flow. This role involves joining established environments, understanding existing architecture and coding patterns, and becoming productive without extensive guidance. The candidate should take ownership of their work, communicate clearly in distributed teams, and bring a thoughtful, detail-oriented approach to data reliability, integration challenges, and production engineering.

Requirements

Bachelor’s Degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related field is desired, or equivalent professional experience.
6+ years of professional experience in Data Engineering, ETL, Data Integration, or a closely related field.
Strong hands-on experience with TypeScript/Node.js in production ETL or data integration environments.
Strong Python experience developing production data pipelines using Dataflow, Airflow, or Cloud Composer.
Hands-on experience with GCP data services, including BigQuery, Cloud Storage, Dataflow, and Pub/Sub.
Proven experience building and maintaining REST API integrations, including OAuth 2.0 authentication, pagination, error handling, and retry logic.
Advanced SQL skills, including complex queries across warehouse schemas for data validation, reconciliation, and analysis.
Experience working with data transformation logic and production data pipelines.
Ability to understand and work within an existing architecture, following established coding patterns, conventions, and CI/CD workflows.
Strong troubleshooting and problem-solving skills across data pipelines, integrations, and cloud environments.
Strong written communication skills and the ability to provide clear updates in an async-first, distributed environment.
Self-directed approach to onboarding, with the ability to become productive within an existing codebase with minimal guidance.
Working English proficiency for collaboration with US-based stakeholders and distributed teams.
6+ years of Data Engineering, ETL, or Data Integration experience.
Strong production experience with TypeScript/Node.js and Python.
Hands-on experience building data pipelines with GCP.
REST API integration and advanced SQL experience.
Experience working with production data pipelines and existing architectures.
English proficiency.

Nice To Haves

Professional experience working with the Zuora REST API.
Experience with ZOQL or Zuora’s billing data model, including subscriptions, invoices, and payments.
Experience with dbt or similar data transformation frameworks.
GCP Professional Data Engineer certification.

Responsibilities

Build, maintain, and enhance production ETL pipelines connecting REST APIs with GCP-based data warehouse environments.
Develop and maintain data integration components using TypeScript/Node.js and Python within an existing pipeline architecture.
Develop data pipelines using GCP services such as BigQuery, Cloud Storage, Dataflow, and Pub/Sub.
Implement transformation logic for billing events, subscription lifecycle data, revenue data, and other data flowing into the GCP data warehouse.
Develop and maintain REST API integrations, including authentication, pagination, error handling, retries, and reliable data extraction.
Support pipeline monitoring and reliability through alerting, logging, error handling, retry mechanisms, and data quality checks.
Write complex SQL queries to support source-to-warehouse data validation, reconciliation, and parity checks.
Collaborate with architecture stakeholders on warehouse-level validation requirements and translate them into SQL checks and reconciliation logic.
Investigate and resolve data pipeline, integration, transformation, and data quality issues.
Follow established coding standards, architecture patterns, CI/CD workflows, and development practices within the existing codebase.
Collaborate with Data Engineering leadership for technical direction while maintaining ownership of assigned development work.
Provide clear written status updates, surface blockers early, and communicate progress effectively within an async-first distributed team.
Contribute to Agile/Kanban workflows while remaining focused on hands-on engineering execution.