Analytics Team Lead

The Senior Lead Analytics Engineer is a strategic and technical leader responsible for designing, building, and optimizing scalable data infrastructure and analytics solutions across company’s marketing technology stack. This role sits at the intersection of data engineering and analytics, empowering marketing and sales teams with high-quality, trusted data to drive insights, campaign performance, and strategic decisions.

A core focus of this role is relational data modeling—the ability to architect clean, scalable, and well-documented data models that reflect complex relationships across marketing platforms such as Salesforce Marketing Cloud, Marketo, and Adobe Marketing Suite. You will work extensively within Medallion architecture using tools like Microsoft Fabric, Power BI, and dbt, ensuring that data is structured in a way that supports intuitive reporting, analytics, and self-service exploration.

Mandatory Skills:

Senior Lead Analytics Engineer – Marketing Technology

Key Responsibilities:

Data Engineering & Relational Modeling

• Partner with the ops ingestion team to build and maintain scalable, efficient data pipelines using Microsoft Fabric and modern ELT tools.
• Design and implement relational data models that accurately represent business entities and their relationships—such as leads, campaigns, touchpoints, and conversions—across multiple marketing platforms.
• Normalize and structure data to reduce redundancy, improve query performance, and ensure consistency across reporting layers.
• Align data models with the Medallion architecture (Bronze, Silver, Gold layers) to support progressive refinement and analytics readiness.
• Integrate and transform data from Salesforce, Marketo, Adobe, and web analytics platforms into a unified, self-service reporting model that supports cross-channel insights and attribution.

Analytics Enablement

• Ensure data accuracy, consistency, and availability across analytics platforms, with the ability to reverse engineer source applications for quality control and user acceptance testing.
• Develop intuitive dashboards and reports that support marketing strategy, campaign performance, and customer journey analytics.

Cross-Functional Collaboration

• Collaborate with marketing strategists, campaign managers, dev-ops, and sales operations to understand data needs and deliver scalable, relationally sound solutions.
• Translate business questions into technical requirements and deliver insights that drive decision-making.

Technical Leadership

• Serve as a subject matter expert in analytics engineering, relational data modeling, and the modern data stack.
• Establish and promote best practices in data development, testing, documentation, and version control, with a focus on model scalability and maintainability.

Tooling & Automation

• Evaluate and implement tools to improve data workflows, observability, and performance using the latest standards and ELT methodologies.
• Automate data validation, transformation, and deployment processes to ensure reliability and repeatability.

Qualifications Required:

• Bachelor’s or master’s degree in computer science, Data Engineering, Marketing Analytics, or a related field.
• 5–8+ years of experience in analytics or data engineering, preferably in a marketing or commercial analytics context.
• Deep expertise in SQL and experience with ELT or similar data modeling tools.
• Proficiency in Microsoft Fabric, including Lakehouses, continuous integration and continuous delivery/deployment, notebooks, pipelines, and Power BI.
• Experience with Salesforce Marketing Cloud, Marketo, and Adobe Marketing Suite.
• Strong understanding of ELT/ETL processes, data warehousing, and data governance.
• Familiarity with Medallion architecture and cloud data platforms (e.g., Adobe CDP, Analytics SDK, Tag Management, and code versioning).
• Experience with Git-based version control and CI/CD for data workflows.

Preferred:

• Hands-on experience designing and deploying relational data models, including star schemas, snowflake schemas, and normalized structures that support scalable analytics.
• Ability to model complex relationships between marketing entities such as campaigns, leads, accounts, and engagement metrics.
• Knowledge of cloud platforms (Azure, AWS, or GCP).
• Strong working knowledge of Salesforce backend development tools such as Workbench and Object Relations Manager.
• Familiarity with marketing attribution models and customer journey analytics.

Key Competencies

• Marketing Data Acumen: Understanding of KPIs, funnel metrics, attribution models, and campaign performance tracking.
• Technical Expertise: Deep knowledge of relational data modeling, transformation, and orchestration tools.
• Analytical Thinking: Proactive approach to identifying and resolving data issues.
• Communication: Ability to translate business needs into technical solutions.
• Initiative: Self-driven and comfortable working independently in a fast-paced, matrixed environment.
• Attention to Detail: High standards for data quality, documentation, and testing.