Director, Analytics

Director, Analytics $215,000-$235,000 + 15-20% bonus Overview A growing enterprise is undertaking a significant transformation of its data and analytics capabilities and is seeking a senior analytics leader to define and execute its analytics platform strategy. This role is ideal for a hands‑on technical leader with deep experience building and delivering production‑grade analytics solutions. The successful candidate will oversee the architecture, development, and operation of a global analytics ecosystem serving both internal stakeholders and external customers. In addition to leading a high‑performing analytics engineering team, this individual will provide technical direction across data warehousing, semantic modeling, embedded analytics, governance, and platform operations. Key Responsibilities Analytics Platform Strategy & Delivery Define and execute the long-term roadmap for a global analytics platform supporting internal reporting and customer‑facing analytics. Drive delivery of analytics products across the full data lifecycle, including ingestion, transformation, warehousing, semantic modeling, and reporting. Design and oversee embedded analytics capabilities integrated into digital products and applications. Establish standards for data architecture, data marts, semantic layers, and governed reporting environments. Ensure platform scalability, reliability, maintainability, and performance. Technical Leadership Serve as the senior technical authority for analytics architecture and engineering decisions. Guide warehouse architecture, cloud data platform strategy, semantic modeling, and BI tool adoption. Provide hands‑on support for performance tuning, optimization, cloud cost management, and operational troubleshooting. Promote modern analytics engineering practices including version control, CI/CD, testing, infrastructure automation, and analytics lifecycle management. Evaluate emerging technologies and recommend solutions that balance innovation with operational stability. Team Leadership & Development Build, mentor, and lead a team of analytics engineers across data engineering, modeling, reporting, and analytics product development. Establish a culture of technical excellence, accountability, collaboration, and continuous improvement. Recruit and develop high‑calibre technical talent. Define career development frameworks, mentorship opportunities, and technical growth pathways. Foster collaboration across engineering, product, business, and operational teams. Data Governance & Operations Implement governance frameworks covering security, access controls, compliance, lineage, and data quality. Establish monitoring, observability, and alerting for analytics platforms and pipelines. Define and manage service‑level objectives for data freshness, platform availability, and reporting performance. Ensure adherence to regulatory and security requirements where applicable. Stakeholder Engagement Partner with executive leaders and business stakeholders to translate strategic objectives into analytics solutions. Act as the primary technical representative for analytics capabilities with customers, partners, and internal teams. Communicate complex technical concepts effectively to both technical and non‑technical audiences. Align analytics initiatives with organisational goals and measurable business outcomes. Required Qualifications Leadership & Experience 10+ years of experience in analytics engineering, data engineering, or related technical disciplines. 5+ years of experience leading and developing analytics or data engineering teams. Proven experience delivering both internal business intelligence solutions and external customer‑facing analytics products. Demonstrated success recruiting, mentoring, and growing technical teams. Data Warehousing & Cloud Platforms Deep expertise with modern cloud data warehouses, particularly Snowflake. Experience with one or more additional data platforms such as Azure Synapse, data lakes, BigQuery, or Redshift. Strong knowledge of at least two major cloud ecosystems (AWS, Azure, and/or GCP) and associated data services. Analytics & Business Intelligence Extensive experience with Looker and semantic‑layer modelling. Advanced proficiency in a modern BI platform such as Looker, Tableau, or Power BI. Experience building embedded analytics solutions integrated into web applications. Data Modeling & Transformation Expert‑level SQL across multiple database platforms. Experience designing governed, reusable semantic models for self‑service analytics. Hands‑on experience with dbt for transformation, testing, and documentation. Familiarity with orchestration and ingestion tools such as Airflow, Fivetran, Informatica, or comparable technologies. Programming & Engineering Strong Python programming skills for analytics engineering, automation, and pipeline development. Knowledge of additional languages such as Scala, Java, or R is beneficial. Solid understanding of Git, CI/CD pipelines, DevOps practices, and software development methodologies. Working familiarity with frontend technologies sufficient to collaborate on embedded analytics initiatives. Governance & Performance Experience implementing data governance controls including RBAC, security policies, lineage, masking, and compliance requirements. Expertise in performance tuning, optimisation, and query diagnostics. Knowledge of data quality testing, observability tooling, and monitoring frameworks. Communication & Leadership Style Excellent written and verbal communication skills. Strong analytical and problem‑solving mindset with a willingness to investigate technical issues directly. Ability to lead effectively in fast‑changing environments with evolving priorities. Preferred Qualifications Experience within a large‑scale service, operations, logistics, transportation, or hospitality‑related environment. Background supporting multi‑tenant analytics environments serving external customers. Experience with infrastructure‑as‑code and containerisation technologies such as Terraform, Docker, and Kubernetes. Understanding of how machine learning or AI solutions can be operationalised within analytics products. Advanced degree in Computer Science, Data Science, Mathematics, Engineering, or a related quantitative field. #J-18808-Ljbffr