Data Engineering Manager

Jobtailor; Colorado; On-site; USD 140,000 - 200,000; Full time

Job summary

Jobtailor in Colorado is seeking a Senior Data Engineering Leader to drive architecture and oversee a growing team. You will guide data ingestion, transformation, and storage across cloud platforms, partnering with data science and IT to deliver scalable data foundations.

The role emphasizes standards, governance, performance, and collaboration, with a focus on building reliable data products and mentoring engineers in best practices.

Qualifications

• Bachelor’s degree in computer science, engineering, information systems, or related field, or equivalent industry experience.
• 3–5 years of experience leading data engineering teams, setting direction and priorities.
• Experience managing budgets and making cost-conscious tool decisions.
• Strong understanding of modern data engineering practices for analytics and AI.
• Extensive experience with data management, transformation, and scalability.

Responsibilities

• Supervising all Data Engineering staff persons.
• Foster professional growth and skill development in their direct reports.
• Delegate tasks and responsibilities effectively, ensuring optimal workload distribution and project efficiency.
• Conduct regular performance evaluations, provide constructive feedback, and set clear goals for direct reports.
• Promote team engagement through regular communication, recognition, and a collaborative, inclusive environment.
• Provide technical and architectural leadership for the data platform, focusing on modern, cloud-based foundations.
• Define and promote best practices for data engineering across the firm, including standards for code quality, testing, deployment, monitoring, and documentation.
• Design, implement, and maintain processes for acquiring, consolidating, and organizing data for downstream use.

Skills

Data Engineering Leadership

Cloud Data Solutions (Azure, AWS)

Advanced SQL Proficiency

Data Management and Transformation

Software Development Life Cycle

Education

Bachelor's degree in CS/Engineering/IS

Graduate degree preferred

Tools

Azure

AWS

Python

Data Visualization Tools

Version Control Systems

Job description

• Supervising all Data Engineering staff persons.
• Foster professional growth and skill development in their direct reports.
• Delegate tasks and responsibilities effectively, ensuring optimal workload distribution and project efficiency.
• Conduct regular performance evaluations, provide constructive feedback, and set clear goals for direct reports.
• Promote team engagement through regular communication, recognition, and a collaborative, inclusive environment.
• Identify training and development opportunities to keep team capabilities current with modern data engineering practices and cloud technologies.
• Provide technical and architectural leadership for the firm’s data platform, with a primary focus on building and operating modern, cloud based data foundations.
• Define and promote best practices for data engineering across the firm, including standards for code quality, testing, deployment, monitoring, and documentation.
• Design, implement, and maintain reliable processes for acquiring, consolidating, and organizing data from core systems and external sources, and making it available for downstream use.
• Ensure that data engineering solutions are scalable, maintainable, and reliable, including management of performance, availability, and capacity risks.
• Partner with Data Science & AI, Information Design & Engineering, IT Operations, and business leaders to understand challenges and translate them into data requirements and platform improvements.
• Contribute to data and AI governance by implementing and enforcing controls for data quality, lineage, access, and responsible use within the data platform.
• Lead the planning, deployment, and ongoing management of data engineering initiatives and related projects.
• Evaluate and prioritize data engineering work based on firm needs, strategic value, and available capacity.
• Manage and document projects, including scope, timelines, risks, dependencies, and key decisions.
• Establish and maintain effective relationships with key technology vendors and service providers that support the data platform.

Requirements

• Bachelor’s degree in computer science, engineering, information systems, or related field, or equivalent industry experience; graduate degree preferred.
• At least 3–5 years of experience leading data engineering or closely related technical teams, including responsibility for setting direction, standards, and priorities.
• Experience managing budgets and making cost conscious decisions about tools, platforms, and services.
• Strong understanding of modern data engineering practices, including data ingestion, consolidation, transformation, and organization to support analytics and AI.
• Extensive experience with data management and data transformation, including performance, reliability, and scalability considerations.
• Advanced SQL experience and strong understanding of how to design and optimize data structures in relational and other data storage technologies.
• Experience designing and managing data solutions in modern cloud environments (for example, Microsoft Azure or Amazon Web Services), including use of platform services.
• Working knowledge of Python and common data tooling, with sufficient depth to review designs and solutions produced by engineers and to engage effectively with Data Science & AI teams.
• Demonstrated experience collaborating with data scientists, analysts, and AI practitioners, and understanding how engineering choices affect downstream analytics and AI work.
• Broad familiarity with data visualization, reporting, and application needs so that data platforms are designed with end to end use in mind, even when this role does not own the final experiences.
• Extensive experience with software development life cycle and software engineering best practices, including version control, testing, deployment, monitoring, and secure handling of data.
• Ability to define and implement data and platform standards, and to guide teams in adopting consistent, high quality engineering practices.

Core Competencies

Demonstrates expertise in leading data engineering teams, implementing modern data practices, and managing cloud-based data solutions. Proficient in data management, transformation, and ensuring data quality while fostering team development and collaboration.

Highest-signal resume keywords

• Data Engineering Leadership
• Cloud Data Solutions (Azure, AWS)
• Advanced SQL Proficiency
• Data Management and Transformation
• Software Development Life Cycle

ATS Optimization Keywords

Hard Skills

• Data Ingestion
• Data Consolidation
• Data Transformation
• Data Organization
• Performance Optimization
• Reliability Engineering
• Scalability Considerations
• Data Quality Control
• Data Lineage
• Data Architecture

Soft Skills

• Team Leadership
• Effective Communication
• Performance Evaluation
• Collaborative Environment
• Constructive Feedback

Industry Keywords

• Data Engineering Best Practices
• Data Governance
• AI Integration
• Data Platform Standards
• Software Engineering Best Practices

Tools & Technologies

• Microsoft Azure
• Amazon Web Services
• Python
• Data Visualization Tools
• Version Control Systems