Lead Data Engineer

Progressive Insurance; United States; Remote; USD 148,000 - 165,000; Full time

Benefits offered by this job

401(k) with company match up to 6%

Medical, dental & vision

Wellness & mental health programs

Health care flexible spending accounts

Life insurance

Paid time off

Parental & family leave

Diversity and inclusion

Tuition assistance

Onsite gym (at large locations)

Job summary

Progressive Insurance is seeking a lead data engineer on the Marketing Data Science and Engineering team to design, develop, and implement scalable data pipelines and cloud infrastructure that power marketing analytics, ML, and AI applications. You will lead engineering standards and mentor peers.

This remote US-based role requires strong AWS, Snowflake, Python, SQL, and CI/CD experience, with a track record of production-ready data platforms and collaboration with data science, governance, and

Qualifications

• Minimum Bachelor’s Degree or higher in IT or related field with at least 5 years designing, programming, and supporting software.
• In lieu of degree, at least 6 years related work experience designing, programming, and supporting software.

Responsibilities

• Lead the design, development, and implementation of scalable data pipelines and cloud infrastructure.
• Build reliable data integration frameworks and establish production-ready engineering practices.
• Mentor engineers and establish engineering standards across the team.

Skills

Python

SQL

Snowflake

Snowpipe

ETL/ELT pipelines

Data modeling

Prefect

dbt

AWS cloud

Terraform

CI/CD

GitHub Actions

Docker

Leadership

Education

Bachelor's degree or higher in Information Technology or related field

Equivalent 6 years of related work experience

Tools

Terraform

EC2

IAM

S3

ECR

Job description

Progressive is dedicated to helping employees move forward and live fully in their careers. Your journey has already begun.

As a lead data engineer on the Marketing Data Science and Engineering team, you’ll lead the design, development, and implementation of scalable data pipelines, cloud infrastructure, and engineering solutions that support marketing analytics, machine learning, and AI applications. In this role, you’ll focus on building reliable data integration frameworks, managing cloud infrastructure, and establishing production-ready engineering practices across the team. You’ll work across the full data engineering lifecycle, from data ingestion and transformation to infrastructure provisioning, deployment, monitoring, and maintenance, while partnering closely with data scientists, data governance teams, enterprise technology teams, and marketing business partners. You’ll provide technical leadership, establish engineering standards, and mentor other engineers to ensure scalable, secure, and maintainable solutions.

This is a remote position for US based work only.

Minimum Qualifications

• Bachelor's Degree or higher in an Information Technology discipline or related field of study and minimum of five years of work experience designing, programming, and supporting software programs or applications.
• In lieu of degree, minimum of six years related work experience designing, programming, and supporting software programs or applications may be accepted.

Preferred Skills

• Strong expertise in AWS cloud infrastructure and Infrastructure as Code (IaC), including Terraform, EC2, IAM, S3, ECR, networking, security configurations, secrets management, and independently provisioning, managing, and troubleshooting scalable cloud environments.
• Strong hands-on experience in data engineering and architecture, with advanced proficiency in Python, SQL, Snowflake, Snowpipe, and designing scalable ETL/ELT pipelines integrating structured and unstructured data from internal systems, external vendors, APIs, and cloud platforms.
• Experience with data transformation, orchestration, and pipeline management, including dbt, Prefect, data modeling, workflow scheduling, incremental processing, automated testing, data quality, pipeline monitoring, troubleshooting, and performance optimization.
• Hands-on experience with DevOps, CI/CD, and production deployment, including GitHub Actions, Docker, containerization, automated deployment pipelines, application integration, monitoring, and production support for machine learning, generative AI, RAG, and agentic AI applications. Experience with secure integration across Snowflake, AWS, and enterprise application hosting environments.
• Ability to provide technical leadership and establish engineering best practices, including solution architecture, code reviews, reusable engineering frameworks, data security and governance controls, cloud cost optimization, production reliability, documentation, mentoring engineers, and collaborating across data science, enterprise IT, governance, and marketing teams.

Compensation

• $148,300 - $164,800/year
• Gainshare annual cash incentive payment up to 40% of your eligible earnings based on company performance

Benefits

• 401(k) with dollar-for-dollar company match up to 6%
• Medical, dental & vision, including free preventative care
• Wellness & mental health programs
• Health care flexible spending accounts, health savings accounts, & life insurance
• Paid time off, including volunteer time off
• Paid & unpaid sick leave where applicable, as well as short & long-term disability
• Parental & family leave; military leave & pay
• Diverse, inclusive & welcoming culture with Employee Resource Groups
• Career development & tuition assistance
• Onsite gym & healthcare at large locations

Energage recognizes Progressive as a 2026 Top Workplace for: Innovation, Purposes & Values, Work-Life Flexibility, Compensation & Benefits, and Leadership.

Equal Opportunity Employer

Applicants must be authorized to work for any employer in the U.S. without the need or potential need, of current or future sponsorship for employment. Progressive does not hire candidates with (e.g., F-1 CPT, OPT, or STEM OPT, H-1B, O-1, E-3, TN) statuses for this role.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.