Lead Analyst, Data & Analytics (Azure Databricks)

Position Overview

The Lead Data Analyst plays a critical role in designing, implementing, and optimizing advanced data analytics solutions to support strategic and operational decision-making. This role partners closely with business, technology, and leadership teams to translate complex data into actionable insights. The position requires strong technical expertise, analytical thinking, and the ability to lead by influence while remaining hands-on with data architecture, analytics, and reporting solutions.

This role is hands-on and requires close collaboration with business and technology teams. The Lead Data Analyst is expected to balance strategic thinking with detailed execution, contribute to architectural decisions, and ensure analytics solutions align with enterprise standards and long-term business objectives.

Key Responsibilities

• Design, develop, and maintain scalable data analytics solutions using Azure Databricks and related enterprise platforms. • Lead data compilation, transformation, integration, and validation from multiple structured and unstructured data sources. • Apply advanced statistical, quantitative, and analytical techniques to identify trends, patterns, and opportunities. • Develop dashboards, reports, and analytical models using Power BI and Databricks AI/BI dashboards. • Define and implement data standards, best practices, and governance processes to ensure data quality and consistency. • Collaborate with cross-functional stakeholders to gather requirements and translate business needs into technical solutions. • Establish processes for monitoring, tracking, and trending data across systems and applications. • Provide peer review and technical guidance on analytics, programming logic, and data modeling. • Support leadership and team members with ad-hoc analysis and strategic insights. • Communicate findings clearly to technical and non-technical audiences.

Technical Skills and Expertise

• Experience with Azure Databricks, Power BI, GitHub, DevOps, and CI/CD pipelines. • Proficiency in PySpark, Python, SQL, and Scala for data engineering, automation, and analytics. • Expertise in data modeling, data mapping, and large-scale data processing. • Experience developing enterprise-grade dashboards and reporting solutions. • Knowledge of cloud-based data architectures and modern analytics platforms.