Senior Staff Data Engineer Jobs
Senior Staff Data Engineer jobs are open across technology, financial services, healthcare, and media, from staff-level to distinguished engineer, with specializations in data platform architecture, streaming pipelines, and analytics infrastructure. Find a role that fits from the openings below and apply directly.
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Job Summary: We are seeking an experienced Senior Staff Engineer – Data & AI Platform to architect and lead our enterprise-wide cloud data modernization and unified AI Platform strategy. In this pivotal technical leadership role, you will spearhead the migration of our data estate from AWS and Databricks to Google Cloud Platform (GCP). You will design and establish standardized ingestion, transformation, and data serving frameworks, build robust developer automation tooling, and lead the architecture of our next-generation enterprise AI and MLOps platform.
Key Responsibilities & Essential Functions:
1. Cloud Migration & Modernization Strategy
- Architect and lead the end-to-end migration of enterprise data workloads and storage from AWS and Databricks to a centralized, modernized GCP ecosystem.
- Establish dual-run strategies, data validation frameworks, and zero-downtime cutover methodologies to ensure business continuity.
- Design multi-tenant, secure, and cost-optimized cloud architectures leveraging BigQuery, Dataflow, Dataproc, and Cloud Storage.
2. Standardized Enterprise Data Frameworks
- Design, build, and evangelize reusable, metadata-driven ingestion, transformation, and serving frameworks.
- Standardize pipeline development with built-in data quality, lineage, automated schema evolution, and enterprise RBAC/governance.
- Create high-performance batch and real-time streaming architectures supporting mission-critical analytics and operational workloads.
3. Developer Experience (DevX) & Automation Tooling
- Build self-service SDKs, templates, and CLI tools that abstract cloud infrastructure complexities for platform consumers (DEs, BIs, DSs).
- Drive CI/CD automation and Infrastructure as Code (IaC) best practices to accelerate time-to-delivery for data and machine learning products.
- Enhance observability, monitoring, alerting, and cost-governance tooling across all data pipelines and AI workloads.
4. AI Platform & MLOps Infrastructure
- Architect and scale enterprise AI and MLOps platforms spanning traditional ML, Deep Learning, and Generative AI (LLMs).
- Implement robust model lifecycle infrastructure including feature stores, model registries, automated CI/CD for ML pipelines, and real-time/batch inference engines.
- Standardize LLMOps foundations, including vector database integration, retrieval-augmented generation (RAG) frameworks, model evaluation pipelines, and fine-tuning infrastructure.
5. Technical Leadership, Governance & Mentorship
- Set technical direction, architectural standards, and engineering guardrails across data and AI engineering teams.
- Mentor senior and staff engineers, fostering technical excellence, innovation, and cross-functional collaboration.
- Partner with Product, Security, Compliance, and Business Leadership to align platform roadmap priorities with core business outcomes.
Technical & Experience Qualifications
- 10+ years of software, data, or platform engineering experience, including 3+ years at the Staff or Senior Staff level.
- Proven success leading large-scale cloud and enterprise data platform migrations.
- Deep expertise in GCP, including BigQuery, Dataflow, Dataproc, Airflow/Composer, Pub/Sub, and GCS.
- Strong experience with Terraform, Kubernetes, and cloud-native infrastructure.
- Hands-on experience building production AI/ML and MLOps platforms using Vertex AI, Kubeflow, MLflow, Feature Stores, and related technologies.
- Knowledge of GenAI, LLMOps, vector databases, RAG, model monitoring, and AI governance.
- Expert proficiency in Python, SQL, Spark, Trino/Presto, and dbt.
- Strong background in distributed systems, data architecture, data modeling, and platform engineering.
- Experience implementing enterprise security, governance, RBAC/ABAC, lineage, auditing, and compliance frameworks.
- Exceptional communication, technical leadership, and stakeholder management skills.
Preferred Qualifications
- Experience with AWS, Databricks, Delta Lake, and Apache Iceberg.
- Experience delivering enterprise-scale cloud modernization and platform transformation initiatives.
- Hands-on experience with production Generative AI, LLM, RAG, and AI Agent solutions.
- Background in retail, supply chain, e-commerce, or other large-scale digital organizations.
- Experience building self-service data and AI platforms and mentoring senior engineering talent.
The responsibilities and essential functions outlined above describe the general nature and level of work assigned to this position. This is not an exhaustive list of all duties, responsibilities, and skills required. Duties and responsibilities may be modified at any time based on business needs. Employees may be required to perform other job-related tasks as requested by their supervisor, subject to reasonable accommodations.
Education:
- Computer Science degree or comparable formal training, certification, or work experience.
Physical Demands & Working Conditions:
- Travel by car or plane with overnight stays
- Work extended hours; sit for extended periods
- Work rotating and on-call schedules, as needed
The work environment characteristics described here are representative of those a Partner encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Last revised: 11/01/2024
Job Summary: We are seeking an experienced Senior Staff Engineer – Data & AI Platform to architect and lead our enterprise-wide cloud data modernization and unified AI Platform strategy. In this pivotal technical leadership role, you will spearhead the migration of our data estate from AWS and Databricks to Google Cloud Platform (GCP). You will design and establish standardized ingestion, transformation, and data serving frameworks, build robust developer automation tooling, and lead the architecture of our next-generation enterprise AI and MLOps platform.
Key Responsibilities & Essential Functions:
1. Cloud Migration & Modernization Strategy
- Architect and lead the end-to-end migration of enterprise data workloads and storage from AWS and Databricks to a centralized, modernized GCP ecosystem.
- Establish dual-run strategies, data validation frameworks, and zero-downtime cutover methodologies to ensure business continuity.
- Design multi-tenant, secure, and cost-optimized cloud architectures leveraging BigQuery, Dataflow, Dataproc, and Cloud Storage.
2. Standardized Enterprise Data Frameworks
- Design, build, and evangelize reusable, metadata-driven ingestion, transformation, and serving frameworks.
- Standardize pipeline development with built-in data quality, lineage, automated schema evolution, and enterprise RBAC/governance.
- Create high-performance batch and real-time streaming architectures supporting mission-critical analytics and operational workloads.
3. Developer Experience (DevX) & Automation Tooling
- Build self-service SDKs, templates, and CLI tools that abstract cloud infrastructure complexities for platform consumers (DEs, BIs, DSs).
- Drive CI/CD automation and Infrastructure as Code (IaC) best practices to accelerate time-to-delivery for data and machine learning products.
- Enhance observability, monitoring, alerting, and cost-governance tooling across all data pipelines and AI workloads.
4. AI Platform & MLOps Infrastructure
- Architect and scale enterprise AI and MLOps platforms spanning traditional ML, Deep Learning, and Generative AI (LLMs).
- Implement robust model lifecycle infrastructure including feature stores, model registries, automated CI/CD for ML pipelines, and real-time/batch inference engines.
- Standardize LLMOps foundations, including vector database integration, retrieval-augmented generation (RAG) frameworks, model evaluation pipelines, and fine-tuning infrastructure.
5. Technical Leadership, Governance & Mentorship
- Set technical direction, architectural standards, and engineering guardrails across data and AI engineering teams.
- Mentor senior and staff engineers, fostering technical excellence, innovation, and cross-functional collaboration.
- Partner with Product, Security, Compliance, and Business Leadership to align platform roadmap priorities with core business outcomes.
Technical & Experience Qualifications
- 10+ years of software, data, or platform engineering experience, including 3+ years at the Staff or Senior Staff level.
- Proven success leading large-scale cloud and enterprise data platform migrations.
- Deep expertise in GCP, including BigQuery, Dataflow, Dataproc, Airflow/Composer, Pub/Sub, and GCS.
- Strong experience with Terraform, Kubernetes, and cloud-native infrastructure.
- Hands-on experience building production AI/ML and MLOps platforms using Vertex AI, Kubeflow, MLflow, Feature Stores, and related technologies.
- Knowledge of GenAI, LLMOps, vector databases, RAG, model monitoring, and AI governance.
- Expert proficiency in Python, SQL, Spark, Trino/Presto, and dbt.
- Strong background in distributed systems, data architecture, data modeling, and platform engineering.
- Experience implementing enterprise security, governance, RBAC/ABAC, lineage, auditing, and compliance frameworks.
- Exceptional communication, technical leadership, and stakeholder management skills.
Preferred Qualifications
- Experience with AWS, Databricks, Delta Lake, and Apache Iceberg.
- Experience delivering enterprise-scale cloud modernization and platform transformation initiatives.
- Hands-on experience with production Generative AI, LLM, RAG, and AI Agent solutions.
- Background in retail, supply chain, e-commerce, or other large-scale digital organizations.
- Experience building self-service data and AI platforms and mentoring senior engineering talent.
The responsibilities and essential functions outlined above describe the general nature and level of work assigned to this position. This is not an exhaustive list of all duties, responsibilities, and skills required. Duties and responsibilities may be modified at any time based on business needs. Employees may be required to perform other job-related tasks as requested by their supervisor, subject to reasonable accommodations.
Education:
- Computer Science degree or comparable formal training, certification, or work experience.
Physical Demands & Working Conditions:
- Travel by car or plane with overnight stays
- Work extended hours; sit for extended periods
- Work rotating and on-call schedules, as needed
The work environment characteristics described here are representative of those a Partner encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Last revised: 11/01/2024
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Find JobsSenior Staff Data Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Hospitality & Tourism
- Investment & Asset Management
- Medical Devices
- Healthcare & Medical Services
What Employers Look For
The qualifications that appear most often in senior staff data engineer jobs.
- 8 or more years of experience building and maintaining large-scale data pipelines
- Deep proficiency with distributed processing frameworks such as Apache Spark or Flink
- Experience designing data platform architecture including lakes, warehouses, and mesh patterns
- Fluency in Python or Scala alongside SQL for transformation and orchestration work
- Hands-on experience with cloud data services on AWS, GCP, or Azure
- Demonstrated ability to lead technical design reviews and mentor senior engineers
Tips for Your Senior Staff Data Engineer Job Search
Quantify pipeline scale on your resume
Hiring managers at the senior staff level care about scope. Replace vague claims with concrete throughput numbers, data volumes, and latency improvements your systems achieved. A resume that names terabyte-scale ingestion or sub-second SLA wins beats one that lists tools alone.
Highlight cross-functional design decisions
Senior staff roles are judged on influence, not just execution. Call out moments when you shaped data contracts with upstream engineering teams, drove schema standards org-wide, or resolved competing platform priorities. That cross-team impact is what separates staff from senior engineers in screening.
Target companies by data maturity stage
A senior staff data engineer at a Series B startup owns different problems than one at a Fortune 500. Filter openings by company size and funding stage to find environments where your strengths, whether greenfield builds or scaling legacy systems, are the actual job.
Apply early to roles that fit
Migrate Mate lists senior staff data engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a system design narrative not a slide deck
Panels for senior staff data engineers almost always include a whiteboard or live design session. Practice walking through a distributed pipeline decision end-to-end: data sources, transformation logic, storage trade-offs, and failure modes. Interviewers want to see how you reason, not just what you built.
Negotiate scope before negotiating title
At the senior staff level, the real negotiation is often around technical scope, team structure, or platform ownership, not just compensation. Before accepting, clarify what systems you will own, whether the role has a reporting path, and what the first six-month mandate actually is.
Senior Staff Data Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most senior staff data engineers?
The companies hiring the most senior staff data engineers right now include ServiceNow, Radar, and Airbnb, with the largest share of openings in California, Washington, and Texas, based on current listings on Migrate Mate as of September 2026. Demand is concentrated in technology, financial services, and healthcare, though openings appear across a wide range of industries.
How many senior staff data engineer jobs are remote?
About 79% of senior staff data engineer openings are fully remote or hybrid as of September 2026, reflecting the distributed nature of modern data platform work. Roles focused on cloud-native infrastructure, streaming pipeline development, and analytics engineering tend to have the highest remote availability compared to positions requiring close collaboration with on-site data science or ML teams.
How do you become a senior staff data engineer?
Reaching the senior staff level typically requires building production data systems at meaningful scale, taking ownership of platform-wide decisions, and demonstrating impact beyond your immediate team. Most engineers get there by leading migrations or re-architecture projects, establishing data standards adopted by other teams, and consistently mentoring senior engineers. A strong foundation in distributed systems, cloud infrastructure, and data modeling underpins all of it.
Can you land a senior staff data engineer role with limited direct experience at that level?
It is possible if you can demonstrate staff-level impact even without the title. Hiring managers look for evidence that you have owned large technical decisions, influenced engineering direction across teams, and shipped systems others depend on. A portfolio of cross-functional projects, open-source contributions to data tooling, or a clear record of technical leadership in a senior engineer role can substitute for a prior staff-level title.
What does the senior staff data engineer interview process look like?
Most processes run three to five rounds. Expect an initial recruiter or hiring manager screen, followed by a technical coding assessment focused on data manipulation or pipeline logic, a system design session where you architect a distributed data solution end-to-end, and a behavioral round assessing cross-functional leadership and influence. Some companies add a presentation round where you walk through a past project at the architecture level.
Where can I find and apply to senior staff data engineer jobs?
You can find and apply to senior staff data engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your experience and specialization, then apply directly to each one that fits.
See All 33 Senior Staff Data Engineer Jobs
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