Lead Data Engineer

Wells Fargo

. Design and implement scalable, secure data platforms on Google Cloud using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Composer .

Posted 9/22/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable data platforms on Google Cloud, utilizing tools such as BigQuery, Dataflow, and Cloud Composer. Proficient in building data ingestion and transformation frameworks while ensuring data quality and governance.

Highest-signal resume keywords

Google Cloud Platform (GCP)BigQueryDataflow/Apache BeamPythonCloud Composer/Airflow

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Database EngineeringData ManagementData Pipeline DevelopmentAutomation ToolingData Quality ChecksDimensional ModelingStreaming IngestionBatch ProcessingError HandlingMonitoring Dashboards

Soft Skills

CollaborationDocumentationFlexibility

Tools & Technologies

Cloud StoragePub/SubCloud BuildGitCloud LoggingCloud Monitoring

Industry Keywords

Agile TransformationsCloud Architecture PrinciplesIAMCost ManagementData Governance

Tech Stack

Tools & technologies

AirflowApacheAWSAzureBigQueryCloudGoogle Cloud PlatformJavaPythonSparkSQLVault

About the role

Key responsibilities & impact

Design and implement scalable, secure data platforms on Google Cloud using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Composer
Build reusable ingestion, transformation, quality, and orchestration frameworks for multiple product and domain teams
Enable self-service data consumption and governance through standardized patterns, templates, and platform capabilities
Design logical and physical data platform architectures using BigQuery, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, and Cloud Storage
Define reusable batch and streaming ingestion, transformation, and serving blueprints
Optimize cost, performance, and reliability of GCP data workloads
Build configuration-driven ingestion frameworks with connectors, schema handling, and error handling
Develop shared Python, SQL, and Beam transformation libraries, including SCD patterns, data quality checks, and masking/tokenization routines
Provide orchestration through Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration
Implement dimensional, data vault, or canonical data models and semantic layers in BigQuery
Enforce data quality, lineage, and observability using standardized metrics, validation rules, and monitoring dashboards
Apply IAM, VPC Service Controls, CMEK, row/column-level security, and policy-driven access patterns
Partner with data engineering, analytics, and ML teams to onboard use cases onto platform services and frameworks
Document patterns, runbooks, and best practices; provide enablement through workshops and code examples
Contribute to platform roadmap, tool selection, and evaluation of new GCP services and open-source components
Provide application development and production support during off-hours

Requirements

What you’ll need

5+ years of Database Engineering experience, or equivalent demonstrated through work experience, training, military experience, or education
5+ years of data management experience within public cloud environments (GCP, AWS, Azure)
5+ years of hands-on experience with Python or Java and Spark SQL for building data pipelines, libraries, and automation tooling
5+ years with orchestration tools such as Cloud Composer/Airflow and CI/CD such as Cloud Build and Git-based workflows for data workloads
Experience with logging and monitoring stacks, including Cloud Logging, Cloud Monitoring, error reporting, and metrics dashboards
Experience with automated testing, data quality checks, and pipeline/platform-service monitoring
Knowledge of cloud architecture principles, including networking, security, IAM, reliability, and cost management
Experience with core GCP data services: BigQuery, Dataflow/Apache Beam, Dataproc, and Pub/Sub
Experience with Agile transformations and technology roadmaps
Experience working with onshore and offshore teams
Flexibility to provide application development and production support during off-hours
This role is not eligible for Visa Sponsorship

Benefits

Comp & perks

Flexible schedule with 3 days in office and 2 days remote
Opportunity to work on cloud-native data platforms supporting analytics and AI at enterprise scale
Workshops, code examples, and enablement opportunities
Equal opportunity employment
Medical accommodation available during recruitment or interview process
Drug-free workplace