Architect and develop robust, scalable ETL/ELT pipelines using Cloud Dataflow, Cloud composer (Airflow), and Pub/Sub for both batch and streaming use cases
Leverage BigQuery as the central data warehouse and design integrations with other GCP services (e.g., Cloud storage, Cloud functions)
Build and optimize analytical data models in BigQuery
Implement partitioning, clustering, and materialized views for performance and cost efficiency
Ensure compliance with data governance, access controls, and IAM best practices
Develop integrations with external systems (APIs, flat files etc.) using GCP-native or hybrid approaches
Utilize tools like Dataflow or custom Python/Java services on Cloud Functions or Cloud Run to handle transformations and ingestion logic
Build automated CI/CD pipeline using Cloud Build, GitHub Actions, or Jenkins for deploying data pipeline code and workflows
Set up observability using Cloud Monitoring, Cloud Logging, and Error Reporting to ensure pipeline reliability
Lead architectural decisions for data platforms and mentor junior engineers on cloud-native data engineering patterns
Promote best practices for code quality, version control, cost optimization, and data security in a GCP environment
Drive initiatives around data democratization, including building reusable datasets and data catalogs via Datapelx or Data Catalog

3+ years of experience with SQL, NoSQL
3+ years of experience with Python (or a comparable scripting language)
3+ years of experience with Data warehouses (such as data modeling and technical architectures) and infrastructure components
3+ years of experience with ETL/ELT, and building high-volume data pipelines
3+ years of experience with reporting/analytic tools
3+ years of experience with Query optimization, data structures, transformation, metadata, dependency, and workload management
3+ years of experience with Big data and cloud architecture
3+ years of hands-on experience building modern data pipelines within a major cloud platform (GCP, AWS, Azure)
3+ years of experience with deployment/scaling of apps on containerized environment (i.e. Kubernetes, AKS)
3+ years of experience with real-time and streaming technology (i.e. Azure Event Hubs, Azure Functions, Kafka, Spark Streaming)
1+ year(s) of soliciting complex requirements and managing relationships with key stakeholders
1+ year(s) of experience independently managing deliverables

Affordable medical plan options
401(k) plan (including matching company contributions)
Employee stock purchase plan
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs
Confidential counseling and financial coaching
Paid time off
Flexible work schedules
Family leave
Dependent care resources
Colleague assistance programs
Tuition assistance
Retiree medical access and many other benefits depending on eligibility

Senior Data Engineer

Key skills