Senior Analytics Engineer

kalibrate; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Kalibrate is seeking a Sr. Analytics Engineer to lead complex analytical initiatives and ensure data readiness across engagements. You will mentor junior engineers, drive process improvements, and ensure scalable, efficient analytical workflows aligned with client objectives.

You will collaborate with Data Science, Customer Success, and Product teams, shaping best practices, delivering high-quality outputs, and advancing automation across analytics operations.

Qualifications

• 6–10 years of analytics or data engineering experience.
• Leadership of complex technical projects.
• Excellent communication and stakeholder management skills.
• Mentoring junior staff and building capability.
• Advanced proficiency with Alteryx and Python.
• Understanding of analytical workflows and model prerequisites.

Responsibilities

• Provide technical leadership and guidance for analytics projects.
• Lead complex data preparation, validation, and integration.
• Ensure quality and reproducibility of analytical outputs.
• Coach associates and analytics engineers through reviews and guidance.
• Drive automation, standardization and continuous improvement.
• Lead technical execution for client engagements and manage risks.
• Collaborate with Data Science, Customer Success and Product teams.

Skills

Analytics leadership

Mentoring

Data transformation

Python

Alteryx

Stakeholder management

Tools

Alteryx

Python

Job description

The Sr. Analytics Engineer is responsible for leading complex analytical engineering initiatives, ensuring data readiness across engagements, and serving as a technical expert within the organization. This role provides technical leadership, mentors junior engineers, drives process improvements, and ensures analytical workflows are scalable, efficient, and aligned with business objectives.

Core Responsibilities:

• Technical Leadership: Serve as a subject matter expert for analytics engineering processes, tools, and best practices while providing guidance to junior team members.
• Complex Data Preparation & Transformation: Lead preparation, validation, and integration of complex 1 st party, 3 rd party, and internal datasets to support advanced analytical solutions.
• Quality Assurance & Delivery Excellence: Establish and enforce quality standards to ensure analytical outputs are accurate, reproducible, and aligned with client requirements.
• Mentorship & Knowledge Sharing: Coach Associate and Analytics Engineers through technical reviews, workflow guidance, and skills development.
• Process Optimization & Innovation: Drive automation, standardization, and continuous improvement initiatives to improve scalability and operational efficiency.
• Project Leadership: Lead technical execution for complex client engagements, coordinate across teams, and proactively manage delivery risks.
• Cross-Functional Partnership: Collaborate closely with Data Science, Customer Success, and Product teams to align analytical execution with business objectives and client expectations

Success Metrics:

• Accuracy and reliability of data outputs
• Successful delivery of complex projects
• Reduction in manual effort and operational inefficiencies
• Adoption of best practices and standardized processes
• Development and mentorship of junior team members
• Stakeholder satisfaction and confidence in deliverables Qualifications

Qualifications:

• 6–10 years of experience in analytics, data engineering, consulting, or related fields
• Advanced proficiency with technical analytical tools (e.g., Alteryx, Python, etc.)
• Strong understanding of model prerequisites and analytical workflows
• Proven experience leading complex technical projects
• Excellent communication and stakeholder management skills
• Experience mentoring junior technical staff Development Expectations Provide technical leadership through influence and expertise, elevate team capabilities through coaching and mentorship, promote best practices, and drive continuous improvement across analytical engineering operations.