Senior Analytics Engineer
Kalibrate
WorldwideremotePosted 23 days ago
Skill Required
Analytics-EngineeringData-EngineeringAnalyticsLocation-IntelligenceSenior-Data-Analytics-EngineerSenior-AI-Analytics-EngineerSenior-Data-And-Insights-EngineerSenior-Data-EngineeringAnalytics-EngineerAnalytics Engineeranalyticsdata engineeringEngineeringanalyticalautomationetc.)PythonandFulltime
Key highlights
- 6–10 years of experience in analytics, data engineering, consulting, or related fields
Role overview
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.
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
Requirements
- 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
Additional details
- Success Metrics: Accuracy and reliability of data outputs
- Success Metrics: Successful delivery of complex projects
- Success Metrics: Reduction in manual effort and operational inefficiencies
- Success Metrics: Adoption of best practices and standardized processes
- Success Metrics: Development and mentorship of junior team members
- Success Metrics: Stakeholder satisfaction and confidence in deliverables
- 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.
- Originally posted on Himalayas