Analytics Head / Data Model Architect

Job Description

Job Title: Analytics Head / Data Model Architect Job Summary: We are seeking a seasoned Analytics Head / Data Model Architect to lead our data strategy, design scalable data models, and drive analytical innovation across the organization. This role combines leadership in data science and business analytics with deep technical expertise in data architecture and modelling. The ideal candidate will be a strategic thinker, technical expert, and effective communicator capable of aligning data initiatives with business objectives. Key Responsibilities: Leadership & Strategy Lead and manage a team of data scientists, analysts, and data architects. Define and drive the enterprise analytics strategy aligned with business goals. Collaborate with executive leadership to identify data-driven growth opportunities. Data Architecture & Modeling Design and implement robust, scalable, and high-performance data models (OLAP/OLTP, dimensional, relational, NoSQL). Develop enterprise data architecture standards, policies, and best practices. Oversee data governance, data quality, and metadata management initiatives. Advanced Analytics & Insights Build advanced analytics solutions including predictive modeling, statistical analysis, and machine learning frameworks. Translate complex data into actionable insights for stakeholders across departments. Evaluate and implement modern BI tools and platforms (e.g., Power BI, Tableau, Looker). Collaboration & Integration Partner with data engineering teams to ensure efficient ETL/ELT pipelines and data lake/warehouse infrastructure. Work closely with business units to understand needs and deliver customized data solutions. Support data privacy, security, and compliance initiatives (e.g., GDPR, HIPAA, SOC 2). Required Qualifications: Bachelor’s or master’s in computer science, Data Science, Statistics, or related field. PhD is a plus. 10+ years of experience in analytics, data architecture, or related roles. Strong knowledge of data modeling techniques (3NF, Star Schema, Snowflake, Data Vault, etc.). Expertise in SQL, Python, R, and at least one cloud platform (AWS, Azure, GCP). Experience with modern data warehousing tools (Snowflake, BigQuery, Redshift) and orchestration (Airflow, DBT). Proven leadership and team-building skills. Preferred Skills: Experience with AI/ML model deployment in production. Familiarity with data mesh, data fabric, or modern data stack concepts. Knowledge of industry-specific data standards (e.g., HL7 for healthcare, ACORD for insurance). Show more Show less