SQL / Python Analytics Manager

As a Lead Data Engineer at Impact Analytics, you will be responsible for designing, building, and automating post-transaction performance reports, executive dashboards, order lifecycle analytics, and pricing & promotion scorecards. Your role will involve partnering with martech and retail media teams, identifying key trends across omnichannel touchpoints, delivering clear recommendations to influence strategies, and collaborating with various teams to align business KPIs and measurement strategies. Key Responsibilities: - Design, build, and automate post-transaction performance reports, including order quality, funnel analytics, and fulfillment metrics. - Develop executive dashboards providing insights on revenue, customer behavior, channel performance, marketing ROI, promotions, and operational KPIs. - Create and maintain detailed Order Lifecycle analytics covering various stages from order creation to post-purchase engagement. - Build Pricing and Promotion scorecards, including elasticity analysis, promo effectiveness, price testing results, and margin impact assessments. - Partner with martech and retail media teams to deliver measurement frameworks and reporting for campaign performance, attribution, and audience segmentation. - Identify key trends, patterns, and business opportunities across omnichannel touchpoints. - Deliver clear recommendations influencing product, merchandising, pricing, CX, and supply-chain strategies. - Translate stakeholder requirements into analytics specifications and prioritize data development needs. - Act as a bridge between business and technical teams, using BI tools and SQL, Python, or R for analytics and automation. - Collaborate with data engineering teams to enhance data models and optimize pipelines. Qualifications Required: - 7-9 years of experience as a Business Analyst or Analytics Specialist in e-commerce, omnichannel retail, martech, or retail media environments. - Strong understanding of e-commerce workflows, digital operations, customer journey, and retail merchandising principles. - Advanced proficiency in SQL and BI visualization tools. - Experience with A/B testing, experimentation platforms, or incrementality measurement. - Knowledge of retail media optimization, digital advertising metrics, and attribution modeling. - Background working with data engineering teams and familiarity with cloud data platforms like Snowflake, BigQuery, Redshift. - Experience supporting pricing, promotion, or merchandising analytics. Please note that Impact Analytics has been recognized for its innovative AI-native SaaS solutions and consulting services that have set new benchmarks in forecasting, planning, and operational excellence across various sectors. The company has received numerous accolades and rankings for its growth, innovation, and contributions to the industry, making it an exciting and dynamic place to work. As a Lead Data Engineer at Impact Analytics, you will be responsible for designing, building, and automating post-transaction performance reports, executive dashboards, order lifecycle analytics, and pricing & promotion scorecards. Your role will involve partnering with martech and retail media teams, identifying key trends across omnichannel touchpoints, delivering clear recommendations to influence strategies, and collaborating with various teams to align business KPIs and measurement strategies. Key Responsibilities: - Design, build, and automate post-transaction performance reports, including order quality, funnel analytics, and fulfillment metrics. - Develop executive dashboards providing insights on revenue, customer behavior, channel performance, marketing ROI, promotions, and operational KPIs. - Create and maintain detailed Order Lifecycle analytics covering various stages from order creation to post-purchase engagement. - Build Pricing and Promotion scorecards, including elasticity analysis, promo effectiveness, price testing results, and margin impact assessments. - Partner with martech and retail media teams to deliver measurement frameworks and reporting for campaign performance, attribution, and audience segmentation. - Identify key trends, patterns, and business opportunities across omnichannel touchpoints. - Deliver clear recommendations influencing product, merchandising, pricing, CX, and supply-chain strategies. - Translate stakeholder requirements into analytics specifications and prioritize data development needs. - Act as a bridge between business and technical teams, using BI tools and SQL, Python, or R for analytics and automation. - Collaborate with data engineering teams to enhance data models and optimize pipelines. Qualifications Required: - 7-9 years of experience as a Business Analyst or Analytics Specialist in e-commerce, omnichannel retail, martech, or retail media environments. - Strong understanding of e-commerce workflows, digital operations, customer journey, and retail merchandising principles. - Advanced proficiency