Analytics Lead, Data Analytics & Modeling
Role details
Job location
Tech stack
Job description
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Design, build, and maintain scalable data models, datasets, and analytical solutions with a focus on correctness, performance, and reusability.
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Write, review, and own production-quality SQL and Python code across data pipelines, transformations, and analytical workflows.
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Serve as a technical lead on complex projects-defining approach, driving design decisions, and ensuring high-quality execution.
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Partner closely with data engineering and platform teams to influence data architecture, modeling standards, and tooling.
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Ensure analytics solutions are built on trusted, well-governed, and sustainable data foundations.
Analytics & Solution Delivery
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Lead the delivery of high-impact dashboards, metrics, and analytical products that support strategic and operational decision-making.
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Translate ambiguous business problems into structured analytical approaches, data models, and technical solutions.
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Apply advanced analytical techniques (e.g., statistical analysis, predictive modeling, machine learning where appropriate) to identify trends, risks, and opportunities.
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Drive automation and standardization of reporting and analytics workflows to improve scalability and reduce manual effort.
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Own outcomes for key deliverables, ensuring timelines, quality, and business impact are met.
Project Leadership & Mentorship
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Lead analytics workstreams across multiple concurrent initiatives, coordinating across stakeholders and ensuring alignment to business priorities.
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Mentor and support junior analysts through code reviews, design discussions, and hands-on coaching.
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Promote best practices in data modeling, coding standards, and analytical rigor across the team.
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Act as a bridge between business stakeholders and technical teams, ensuring solutions are both business-relevant and technically sound.
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Contribute to shaping analytics priorities and roadmaps, balancing near-term delivery with long-term data quality and scalability.
Requirements
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4+ years of experience in data analytics, data engineering, or related technical roles with strong hands-on delivery.
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Proven experience leading complex analytics or data initiatives as an individual contributor.
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Strong experience designing scalable data models (e.g., dimensional, semantic, or analytical models).
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Advanced proficiency in SQL and Python, with experience maintaining complex analytical codebases.
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Experience partnering closely with data engineering teams on data pipelines, architecture, and data platforms.
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Deep understanding of analytics and BI concepts, with experience using tools such as Power BI, Tableau, Looker, or similar.
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Strong ability to translate ambiguous business problems into well-structured technical solutions.
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Excellent communication skills, with the ability to clearly explain technical concepts to both technical and non-technical audiences.
Preferred Experience:
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Experience mentoring analysts in a technical lead or informal leadership capacity.
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Familiarity with modern data platforms (e.g., cloud data warehouses, transformation frameworks, orchestration tools).
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Experience operating in complex, enterprise or regulated environments.
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Background in financial services, wealth management, or advisor-focused businesses.