Lead Data Engineer

Wells Fargo

Lead Data Engineer developing scalable, secure data platforms on Google Cloud. Designing architectures and reusable frameworks for data capabilities at Wells Fargo.

Posted 6/3/2026full-timeIselin • New Jersey, North Carolina, Texas • 🇺🇸 United StatesSenior💰 $119,000 - $224,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowApacheAWSAzureBigQueryCloudGoogle Cloud PlatformJavaPythonSparkSQLVault

About the role

Key responsibilities & impact

Design and implement scalable, secure data platforms on Google Cloud using managed services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Composer).
Build reusable frameworks and tooling (ingestion, transformation, quality, orchestration) that can be adopted by multiple product and domain teams.
Enable self‑service data consumption and governance by standardizing patterns, templates, and platform capabilities rather than one‑off pipelines.
Design logical and physical data platform architectures leveraging BigQuery, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, and Cloud Storage.
Define and implement standardized ingestion, transformation, and serving patterns (batch and streaming) as reusable blueprints.
Optimize cost, performance, and reliability of GCP data workloads (partitioning, clustering, storage classes, autoscaling strategies).
Build opinionated data ingestion frameworks (e.g., config‑driven pipelines, connectors, schema handling, error handling) on top of Dataflow, Dataproc, or Composer.
Develop shared transformation libraries in Python/SQL/Beam (e.g., common SCD patterns, data quality checks, masking/tokenization routines).
Provide orchestration capabilities via Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration.
Implement robust data modeling (dimensional, data vault, or canonical models) and semantic layers in BigQuery and related tools.
Enforce data quality, lineage, and observability using standardized metrics, validation rules, and monitoring dashboards.
Apply security and governance controls: IAM, VPC‑SC, CMEK, row/column‑level security, and policy‑driven access patterns
Partner with domain data engineers, analytics, and ML teams to onboard use cases onto platform services and frameworks
Document patterns, runbooks, and best practices, and provide enablement through workshops and code examples.
Contribute to platform roadmap, tool selection, and evaluation of new GCP services and open‑source components.

Requirements

What you’ll need

5+ years of Database Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of data management experience within Public Cloud (GCP, AWS, Azure)
5+ years of hands on experience of Python or Java, plus Spark SQL for building data pipelines, libraries, and automation tooling.
5+ years with orchestration tools (Cloud Composer/Airflow) and CI/CD (Cloud Build, Git‑based workflows) for data workloads

Benefits

Comp & perks

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data platform designdata ingestiondata transformationdata qualitydata modelingPythonSQLJavaSpark SQLCI/CD

Soft Skills

collaborationdocumentationworkshop facilitationproblem-solvingcommunication