Mid Level Data Architect Jobs
Mid level data architect jobs call for professionals ready to own data modeling initiatives end to end, guide junior teammates, and make design decisions with minimal oversight. About 42% of openings are remote or hybrid, with roles concentrated across Technology & Software, Consulting & Professional Services, and Distribution & Wholesale and employers like Amazon Web Services, Amazon, and AECOM hiring at this level now.
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Build the Future of Connected Vehicle Data at Stellantis
Stellantis is transforming the future of mobility through connected vehicles, advanced
analytics, artificial intelligence, and data-driven products. Our AI & Data Analytics team
develops scalable platforms and innovative data solutions that power some of the world's
most recognized automotive brands.
We are seeking a Senior Data Solutions Architect to lead the design and implementation of
enterprise-scale data products and platforms. This role combines technical leadership,
architecture, cloud engineering, and stakeholder collaboration to deliver secure, scalable,
and high-performance data solutions that support both internal software products and
external customer offerings.
If you are passionate about cloud architecture, big data technologies, real-time data
processing, and building modern data platforms from the ground up, we'd like to hear from
you.
About the Role
As a Senior Data Solutions Architect, you will serve as a technical leader responsible for
defining architecture, driving technology decisions, and building scalable data services
that support Stellantis' connected vehicle ecosystem.
You will be a partner with engineering, product, analytics, and business teams to develop
modern cloud-based data platforms, establish engineering best practices, and ensure
data quality across the organization.
This role requires expertise in data architecture, cloud technologies, and distributed
processing systems, real-time data pipelines, and large-scale data engineering.
What You'll Do
Data Architecture & Solution Design
Lead the architecture and technical design of enterprise data solutions for internal
platforms and customer-facing products.
Design and implement secure, scalable, resilient, and high-performance data
services using modern cloud and Big Data technologies.
Define architecture standards and engineering best practices for data platforms
and analytics solutions.
Evaluate technology options and make architecture decisions that align with
business and technical objectives.
Cloud & Big Data Engineering
Design and implement distributed data processing solutions using cloud-native
technologies.
Build scalable data pipelines for ingestion, transformation, validation, and delivery
of connected vehicle data.
Develop real-time and batch processing architectures that support growing
business needs.
Ensure data platforms meet performance, reliability, scalability, and security
requirements.
Technical Leadership
Provide technical direction across multiple engineering teams.
Influence architectural decisions and drive alignment across cross-functional organizations.
Lead implementation efforts from concept through production deployment.
Mentor and support engineers and technical team members to help grow organizational capabilities.
Data Quality & Operational Excellence
Establish and maintain data quality standards, validation processes, and
monitoring frameworks.
Lead efforts to standardize instrumentation, observability, and operational
readiness across software platforms.
Develop comprehensive documentation, runbooks, and troubleshooting
processes.
Drive continuous improvement initiatives across data engineering and platform operations.
Stakeholder Collaboration
Partner with product, engineering, analytics, and business teams to understand
complex requirements and deliver effective solutions.
Build strong relationships with upstream and downstream stakeholders to ensure
successful delivery of data products.
Translate technical concepts into clear business outcomes and recommendations.
Requirements:
Required Qualifications
Education
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline.
Experience
5+ years of experience in data engineering, software development, or data platform architecture.
4+ years of hands-on experience building and maintaining production-grade data applications.
4+ years of experience working with AWS cloud services in production environments.
Experience designing and implementing enterprise-scale data solutions and platforms.
Technical Skills
Data Architecture & Engineering
Data architecture and data modeling
Relational and columnar database technologies
Operational data stores
Master data management
ETL and ELT design, implementation, and optimization
Data quality management and validation frameworks
Cloud & Big Data Technologies
AWS cloud services
Apache Spark
Distributed data processing platforms
Programming Languages
Python
Java
Streaming & Real-Time Data
Notification Event Bus
Kinesis
SNS (Simply Notification Service)
SQS (Simple Queue Service)
MQ (Message Queue)
Data Orchestration & Workflow Management
Apache Airflow
Azure Data Factory
Workflow orchestration platforms
API & Platform Development
API design and development
Data service architecture
Integration patterns and distributed systems
Leadership Skills
Experience leading cross-functional technical initiatives.
Ability to architect solutions from concept through implementation.
Strong communication skills with the ability to translate complex technical concepts into business-focused solutions.
Experience mentoring and guiding engineering teams.
Preferred Qualifications
AWS certification or equivalent cloud certification.
Experience with Databricks and Databricks notebook workflows.
Experience with Infrastructure as Code (IaC) tools such as Terraform.
Experience supporting enterprise analytics, machine learning, or AI-driven platforms.
Experience working with connected vehicle, IoT, or large-scale telemetry data
Build the Future of Connected Vehicle Data at Stellantis
Stellantis is transforming the future of mobility through connected vehicles, advanced
analytics, artificial intelligence, and data-driven products. Our AI & Data Analytics team
develops scalable platforms and innovative data solutions that power some of the world's
most recognized automotive brands.
We are seeking a Senior Data Solutions Architect to lead the design and implementation of
enterprise-scale data products and platforms. This role combines technical leadership,
architecture, cloud engineering, and stakeholder collaboration to deliver secure, scalable,
and high-performance data solutions that support both internal software products and
external customer offerings.
If you are passionate about cloud architecture, big data technologies, real-time data
processing, and building modern data platforms from the ground up, we'd like to hear from
you.
About the Role
As a Senior Data Solutions Architect, you will serve as a technical leader responsible for
defining architecture, driving technology decisions, and building scalable data services
that support Stellantis' connected vehicle ecosystem.
You will be a partner with engineering, product, analytics, and business teams to develop
modern cloud-based data platforms, establish engineering best practices, and ensure
data quality across the organization.
This role requires expertise in data architecture, cloud technologies, and distributed
processing systems, real-time data pipelines, and large-scale data engineering.
What You'll Do
Data Architecture & Solution Design
Lead the architecture and technical design of enterprise data solutions for internal
platforms and customer-facing products.
Design and implement secure, scalable, resilient, and high-performance data
services using modern cloud and Big Data technologies.
Define architecture standards and engineering best practices for data platforms
and analytics solutions.
Evaluate technology options and make architecture decisions that align with
business and technical objectives.
Cloud & Big Data Engineering
Design and implement distributed data processing solutions using cloud-native
technologies.
Build scalable data pipelines for ingestion, transformation, validation, and delivery
of connected vehicle data.
Develop real-time and batch processing architectures that support growing
business needs.
Ensure data platforms meet performance, reliability, scalability, and security
requirements.
Technical Leadership
Provide technical direction across multiple engineering teams.
Influence architectural decisions and drive alignment across cross-functional organizations.
Lead implementation efforts from concept through production deployment.
Mentor and support engineers and technical team members to help grow organizational capabilities.
Data Quality & Operational Excellence
Establish and maintain data quality standards, validation processes, and
monitoring frameworks.
Lead efforts to standardize instrumentation, observability, and operational
readiness across software platforms.
Develop comprehensive documentation, runbooks, and troubleshooting
processes.
Drive continuous improvement initiatives across data engineering and platform operations.
Stakeholder Collaboration
Partner with product, engineering, analytics, and business teams to understand
complex requirements and deliver effective solutions.
Build strong relationships with upstream and downstream stakeholders to ensure
successful delivery of data products.
Translate technical concepts into clear business outcomes and recommendations.
Requirements:
Required Qualifications
Education
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline.
Experience
5+ years of experience in data engineering, software development, or data platform architecture.
4+ years of hands-on experience building and maintaining production-grade data applications.
4+ years of experience working with AWS cloud services in production environments.
Experience designing and implementing enterprise-scale data solutions and platforms.
Technical Skills
Data Architecture & Engineering
Data architecture and data modeling
Relational and columnar database technologies
Operational data stores
Master data management
ETL and ELT design, implementation, and optimization
Data quality management and validation frameworks
Cloud & Big Data Technologies
AWS cloud services
Apache Spark
Distributed data processing platforms
Programming Languages
Python
Java
Streaming & Real-Time Data
Notification Event Bus
Kinesis
SNS (Simply Notification Service)
SQS (Simple Queue Service)
MQ (Message Queue)
Data Orchestration & Workflow Management
Apache Airflow
Azure Data Factory
Workflow orchestration platforms
API & Platform Development
API design and development
Data service architecture
Integration patterns and distributed systems
Leadership Skills
Experience leading cross-functional technical initiatives.
Ability to architect solutions from concept through implementation.
Strong communication skills with the ability to translate complex technical concepts into business-focused solutions.
Experience mentoring and guiding engineering teams.
Preferred Qualifications
AWS certification or equivalent cloud certification.
Experience with Databricks and Databricks notebook workflows.
Experience with Infrastructure as Code (IaC) tools such as Terraform.
Experience supporting enterprise analytics, machine learning, or AI-driven platforms.
Experience working with connected vehicle, IoT, or large-scale telemetry data
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Find Mid Level Data Architect JobsMid Level Data Architect Job Market
Who's Hiring
- Amazon Web Services8
- Amazon4
- AECOM3
- NeuraFlash3
- JPMorganChase3
Top Industries Hiring
- Technology & Software26
- Consulting & Professional Services14
- Distribution & Wholesale9
- Insurance7
- Banking & Financial Services7
Mid Level Data Architect Jobs: Frequently Asked Questions
How do I get a mid level data architect job?
Position yourself around ownership, not just participation. Highlight projects where you made architectural decisions, led data modeling efforts, or improved pipeline reliability without being told exactly what to do. Concrete outcomes matter more than job titles. Tailor your resume to show depth in a specific stack, whether cloud data platforms, dimensional modeling, or data mesh patterns, and demonstrate that you can operate with limited day-to-day direction.
Which companies hire mid level data architects?
Companies hiring mid level data architects right now include Amazon Web Services, Amazon, and AECOM, based on current listings on Migrate Mate as of July 2026. Hiring at this level comes from a wide range of employers, including large enterprises modernizing legacy systems, fast-growing technology companies scaling their data infrastructure, and consulting firms staffing client-facing data initiatives.
Are there remote mid level data architect jobs?
Yes, remote and hybrid options are common at this level. About 42% of mid level data architect openings are remote or hybrid as of July 2026, reflecting how effectively this work translates to distributed teams. Fully on-site roles still exist, particularly at financial institutions and regulated industries, so the mix depends on the sector and employer.
How do I move up to a mid level data architect role?
The progression from entry level to mid level is built on demonstrated ownership over time. Focus on taking full responsibility for at least one end-to-end data modeling or pipeline project, learning to evaluate architectural trade-offs, and building fluency with enterprise data tools beyond your initial stack. Contributing to documentation, code reviews, and junior onboarding signals that you are ready to operate at mid level scope and influence.
Which industries hire the most mid level data architects?
Mid Level data architect roles concentrate in Technology & Software, Consulting & Professional Services, and Distribution & Wholesale, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring at this level because they manage large, complex, and often regulated datasets that require professionals who can design scalable data systems and translate business requirements into durable architecture.