Senior Technical Product Manager, Data Engineering Solutions

Jobtailor; Colorado; On-site; USD 180,000 - 230,000; Full time

Job summary

Jobtailor is seeking a senior product leader to shape the data platform strategy across onboarding, storage, and core services, partnering with data and engineering teams to deliver scalable analytics and AI capabilities. You will own the platform's resiliency, disaster recovery, and operational readiness, and collaborate on model lifecycle management and MLOps to drive enterprise-wide impact.

This role demands deep cloud experience (Databricks, Snowflake, AWS/Azure/GCP) and a proven ability to

Qualifications

• 7+ years of product management or related roles.
• Strong understanding of cloud-native architectures and enterprise platforms.
• Experience with Databricks, Snowflake, or similar data platforms.
• Experience with SDLC, Agile, and DevOps practices.
• Ability to align software, data, and platform teams with business goals.

Responsibilities

• Drive product strategy and roadmap for data platform capabilities.
• Lead cross-functional teams delivering scalable analytics and AI solutions.
• Partner with stakeholders to define requirements for data platform capabilities.
• Own product vision for platform resiliency, disaster recovery, and operational readiness.
• Collaborate with engineering to evolve ML/AI platform capabilities including MLOps.

Skills

Product Management

Cloud-Native Architectures

Data Engineering

Machine Learning Operations

Stakeholder Management

Cross-functional Leadership

SDLC Methodologies

Agile

DevOps Practices

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field

Advanced degree preferred

Tools

Databricks

Snowflake

AWS

Azure

Google Cloud Platform

Delta Lake

MLflow

Databricks SQL

Job description

• Drive product strategy and roadmap for critical data and platform capabilities, including data onboarding, storage solutions, and core platform services
• Lead cross-functional teams to deliver shared data engineering capabilities enabling scalable, enterprise-wide analytics and AI solutions
• Partner with stakeholders to define requirements for common data platform capabilities, pipeline tooling, and developer experiences used across enterprise data workflows
• Own product vision for platform resiliency, disaster recovery, and operational readiness to ensure reliability, scalability, and business continuity
• Collaborate with engineering teams to evolve machine learning and AI platform capabilities, including model lifecycle management and MLOps practices

Requirements

• 7+ years of experience in product management, or a combination of product management and technical roles, delivering complex software, platform, data, or infrastructure solutions
• Strong understanding of cloud-native architectures, software platforms, and enterprise technology ecosystems
• Familiarity with modern data platforms such as Databricks, Snowflake, or similar technologies used for large-scale data processing and analytics
• Familiarity with data platforms, data pipelines, analytics workflows, or related technical concepts
• Working knowledge of SDLC methodologies, including Agile and DevOps practices
• Ability to engage effectively with software, platform, and data engineering teams on technical architecture, platform capabilities, and product tradeoffs
• Strong communication and stakeholder management skills
• Proven ability to define product vision, prioritize investments, and deliver measurable business outcomes
• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience
• Experience with Databricks technologies, including Delta Lake, MLflow, Databricks SQL, or similar lakehouse capabilities
• Experience supporting data engineering, analytics, machine learning, AI, or platform products
• Understanding of machine learning concepts, model lifecycle processes, and MLOps practices
• Prior experience in software engineering, data engineering, analytics engineering, or related technical disciplines
• Experience with AWS, Azure, or Google Cloud Platform
• Exposure to enterprise data quality, resiliency, governance, metadata management, or related platform initiatives
• Experience working with internal platforms, developer platforms, or shared enterprise capabilities
• Advanced degree in a technical or business-related discipline is preferred

Core Competencies

Demonstrates expertise in product management and technical roles, focusing on data platform capabilities, cloud-native architectures, and machine learning operations. Proven ability to lead cross-functional teams and engage stakeholders to deliver scalable analytics solutions and ensure platform resiliency.

Highest-signal resume keywords

• Product Management
• Cloud-Native Architectures
• Data Engineering
• Machine Learning Operations
• Stakeholder Management

ATS Optimization Keywords

Hard Skills

• Data Onboarding
• Data Storage Solutions
• Data Pipeline Tooling
• Analytics Workflows
• SDLC Methodologies
• Agile Practices
• DevOps Practices
• Model Lifecycle Management
• MLOps Practices
• Enterprise Technology Ecosystems

Soft Skills

• Strong Communication
• Effective Engagement

Industry Keywords

• Data Quality
• Platform Resiliency
• Governance
• Metadata Management
• Enterprise Data Workflows

Tools & Technologies

• Databricks
• Snowflake
• AWS
• Azure
• Google Cloud Platform
• Delta Lake
• MLflow
• Databricks SQL