Data Modeler/Data Analyst

Job Description

Job Summary We are looking for a seasoned Data Modeler / Data Analyst to design and implement scalable, reusable logical and physical data models on Google Cloud Platformprimarily BigQuery. You will partner closely with data engineers, analytics teams, and business stakeholders to translate complex business requirements into performant data models that power reporting, self-service analytics, and advanced data science workloads. Key Responsibilities Gather and analyze business requirements to translate them into conceptual, logical, and physical data models on GCP (BigQuery, Cloud SQL, Cloud Spanner, etc.). Design star/snowflake schemas, data vaults, and other modeling patterns that balance performance, flexibility, and cost. Implement partitioning, clustering, and materialized views in BigQuery to optimize query performance and cost efficiency. Establish and maintain data modelling standards, naming conventions, and metadata documentation to ensure consistency across analytic and reporting layers. Collaborate with data engineers to define ETL/ELT pipelines and ensure data models align with ingestion and transformation strategies (Dataflow, Cloud Composer, Dataproc, dbt). Validate data quality and lineage; work with BI developers and analysts to troubleshoot performance issues or data anomalies. Conduct impact assessments for schema changes and guide version-control processes for data models. Mentor junior analysts/engineers on data modeling best practices and participate in code/design reviews. Contribute to capacity planning and cost-optimization recommendations for BigQuery datasets and reservations. Must-Have Skills 6-8 years of hands-on experience in data modeling, data warehousing, or database design, including at least 2 years on GCP BigQuery. Proficiency in dimensional modeling, 3NF, and modern patterns such as data vault. Expert SQL skills with demonstrable ability to optimize complex analytical queries on BigQuery (partitioning, clustering, sharding strategies). Strong understanding of ETL/ELT concepts and experience working with tools such as Dataflow, Cloud Composer, or dbt. Familiarity with BI/reporting tools (Looker, Tableau, Power BI, or similar) and how model design impacts dashboard performance. Experience with data governance practices—data cataloging, lineage, and metadata management (e.g., Data Catalog). Excellent communication skills to translate technical concepts into business-friendly language and collaborate across functions. Good to Have Experience of working on Azure Cloud (Fabric, Synapse, Delta Lake) Education Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, Statistics, or a related field. Equivalent experience will be considered.