Mid Level Solutions Engineering Manager Jobs
Mid level solutions engineering manager jobs go to professionals ready to own complex client engagements, guide junior teammates, and shape technical solutions with limited day-to-day oversight. Openings run across Technology & Software, Electronics & Hardware, and Retail, with 19% remote or hybrid availability, and employers like Apple, Esri, and Notion 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 JobsMid Level Solutions Engineering Manager Job Market
Who's Hiring
- Apple7
- Esri5
- Notion4
- Amazon4
- Emerson2
Top Industries Hiring
- Technology & Software18
- Electronics & Hardware8
- Retail4
- E-Commerce & Online Marketplaces4
- Insurance2
Mid Level Solutions Engineering Manager Jobs: Frequently Asked Questions
How do I get a mid level solutions engineering manager job?
Position yourself around the complexity you have already handled, not just the time you have spent. Highlight client-facing wins where you drove the technical conversation, deals you helped close, and any cross-functional coordination you led. Mid level hiring managers want to see that you can manage a solution cycle with real independence, so lead your resume and interviews with outcomes and scope, not tasks.
Which companies hire mid level solutions engineering managers?
Companies hiring mid level solutions engineering managers right now include Apple, Esri, and Notion, based on current listings on Migrate Mate as of July 2026. Both established enterprise software vendors and growth-stage SaaS companies tend to hire actively at this level, as they need professionals who can run pre-sales cycles and customer onboarding without heavy senior oversight.
Are there remote mid level solutions engineering manager jobs?
Yes, though availability varies by employer and industry. About 19% of mid level solutions engineering manager openings are remote or hybrid as of July 2026, making this one of the more flexible roles in technical go-to-market functions. Fully on-site positions tend to appear at companies with complex enterprise deployments that require frequent hands-on customer visits.
How do I move up to a mid level solutions engineering manager role?
The progression from entry level to mid level in solutions engineering management comes from accumulating ownership over full sales or implementation cycles, not just supporting them. Build depth by leading discovery calls, managing proof-of-concept projects end to end, and taking measurable accountability for outcomes. Demonstrating that you can coordinate across product, sales, and customer success teams, and point to deals influenced or retained, is what moves you into mid level territory.
Which industries hire the most mid level solutions engineering managers?
Mid Level solutions engineering manager roles concentrate in Technology & Software, Electronics & Hardware, and Retail, based on current listings on Migrate Mate as of July 2026. These sectors tend to sell technically complex products where mid level solutions engineering managers serve as the bridge between a customer's operational needs and the vendor's product capabilities, making the role critical to both acquisition and retention.