Senior Data Analytics Engineering Lead

Optomi, in partnership with a leading technology organization, is seeking a Senior Data Analytics Engineering Lead to join a highly visible team responsible for driving analytics, reporting, instrumentation, and data-driven decision making across multiple lines of business. This individual will serve as a trusted advisor to stakeholders, owning critical metrics from definition through delivery while building scalable data solutions that enable business growth. The ideal candidate combines strong analytics expertise, hands-on data engineering experience, and exceptional communication skills to translate complex data into actionable business insights.

• 8+ years of experience in analytics, data engineering, instrumentation, business intelligence, and/or data visualization. \n

• Advanced SQL expertise with the ability to analyze and transform complex datasets. \n

• Strong hands-on experience utilizing Spark within enterprise-scale data environments. \n

• Experience building and maintaining scalable data and metrics pipelines. \n

• Proven experience creating instrumentation specifications and partnering with engineering teams on data collection strategies. \n

• Strong background in data validation, quality assessment, root-cause analysis, and reporting accuracy. \n

• Experience designing dashboards and executive-facing visualizations. \n

• Hands-on experience leveraging AI tools for data exploration, mining, and analytics workflows. \n

• Demonstrated ability to manage multiple business functions and stakeholder groups with minimal oversight. \n

• Strong executive communication skills with the ability to present technical findings to non-technical audiences. \n

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• Owning business-critical metrics and analytics initiatives with significant visibility across the organization. \n

• Serving as a trusted advisor to business leaders, engineers, and executive stakeholders. \n

• Building scalable data pipelines and analytics solutions that directly impact business decisions. \n

• Working with large-scale datasets using modern technologies such as SQL, Spark, and AI-powered analytics tools. \n

• Operating with a high degree of autonomy and ownership while managing multiple business domains. \n

• Solving complex data quality, instrumentation, and reporting challenges. \n

• Presenting findings and recommendations directly to senior leadership and influencing strategic initiatives. \n

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Experience of the right candidate:

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• Own analytics, reporting, and KPI development across multiple lines of business. \n

• Define key performance indicators and measurement frameworks aligned with business objectives. \n

• Create clear instrumentation specifications to ensure accurate and reliable data collection. \n

• Design, build, and maintain scalable metrics and data pipelines using SQL, Spark, and modern data engineering practices. \n

• Conduct data validation, quality assessments, and root-cause analysis to identify and resolve reporting discrepancies. \n

• Perform exploratory analysis and uncover trends, patterns, and opportunities within large datasets. \n

• Develop dashboards, scorecards, and executive-facing visualizations that drive informed decision-making. \n

• Leverage AI-powered tools and technologies to accelerate data exploration, analysis, and insight generation. \n

• Partner with business leaders, engineering teams, and analytics stakeholders to translate business requirements into actionable data solutions. \n

• Present insights, recommendations, and findings to executives and non-technical audiences. \n

• Act as the primary point of contact for data, metrics, and reporting within assigned business areas. \n

• Identify opportunities to improve data quality, operational reporting, and analytics processes across the organization. \n

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