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Senior Analytics Engineer

Role overview

Qualifications

  • Technical expertise in analytics engineering
  • Experience in data preparation and transformation
  • Strong leadership and mentorship skills
  • Knowledge of quality assurance standards

Responsibilities

  • Serve as a subject matter expert for analytics engineering processes
  • Lead preparation and integration of complex datasets
  • Establish quality standards for analytical outputs
  • Drive process improvements for operational efficiency

Key facts

  • Remote from: Texas (USA)
  • Full time
  • Senior (5-10 years)
  • English

Other skills

  • Quality Assurance
  • Mentorship
  • Collaboration
  • Problem Solving
  • Communication

About the company

Kalibrate logo

Kalibrate

Computer Software / SaaS

We remove the guesswork from organizations' biggest location-based decisions. Through our data, software, and consulting, we help businesses in a range of industries invest with confidence, manage risk, and get ahead of the competition. For decades, we've been the trusted decision-making partner for the world's leading brands. Today, Kalibrate supports 800+ organizations in over 70 countries. We are headquartered in Manchester UK, with offices globally.

Company details

Company typeScaleup
IndustryComputer Software / SaaS
Company size201 - 500

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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


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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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