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Data Modeler

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Modeler on a long-term contract ($45–$63/hour) in NYC, requiring 3+ years of experience, advanced SQL, Python, AWS proficiency, and strong data modeling skills within a medallion architecture.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
504
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🗓️ - Date
August 1, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
New York, NY
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🧠 - Skills detailed
#PySpark #Apache Spark #Statistics #CRM (Customer Relationship Management) #API (Application Programming Interface) #Computer Science #Data Aggregation #Datasets #Snowflake #Data Engineering #Python #AWS (Amazon Web Services) #SQL (Structured Query Language) #AI (Artificial Intelligence) #Airflow #Data Modeling #Spark (Apache Spark) #ChatGPT
Role description
Data Modeler, Data Analytics (Consultant) — Long-Term Contract A well-known, high-profile organization headquartered in Midtown Manhattan is seeking a Data Modeler to join its Data Analytics team as part of a next-generation data platform initiative — one that will power personalized content and offerings for a large, engaged audience through advanced analytics. This is a long-term contract opportunity, $45–$63/hour based on experience, NYC preferred (4 days onsite). This role sits within an AWS-based medallion architecture (bronze, silver, gold). While the Data Engineering team owns ingestion and the bronze/silver layers, this role picks up from the curated gold layer downward — designing and building the analytical data models, aggregations, and reporting structures that power business insight across the organization. The ideal candidate is, first and foremost, an excellent data modeler, and second, someone who can quickly learn and internalize the business context behind the models they build — whether that's sales, engagement, or growth initiatives. This role also makes heavy use of AI-assisted development tools (ChatGPT, Codex, and Claude within AWS) and should be strong in prompt engineering. Responsibilities: • Design, build, and maintain dimensional and analytical data models (fact and dimension tables, semantic layers, aggregates) on top of the gold layer within an AWS medallion architecture, using advanced SQL, Python, PySpark, Airflow, and Apache Spark • Build reporting and data aggregation logic supporting multi-dimensional analysis across business functions including sales, engagement, and growth • Develop and maintain API-based data retrieval processes to bring in additional business data (e.g., ticketing/transactional systems, CRM platforms, market research sources) into the analytics layer • Partner closely with business stakeholders to understand the concepts and goals behind each modeling request, translating business needs into accurate, well-structured, reusable data models • Collaborate with the Data Engineering team to ensure gold-layer data structures are well-suited to downstream modeling and reporting needs • Leverage AI coding assistants (ChatGPT, Codex, Claude within AWS) as a core part of the modeling workflow, using strong prompt engineering to accelerate model design, query development, and validation • Apply data modeling fundamentals to evaluate and refine AI-generated solutions, ensuring models correctly represent business logic and produce accurate, trustworthy metrics • Document data models, definitions, and business logic to keep models understandable and maintainable across teams Requirements: • Bachelor's degree in computer science, data analytics, statistics, or a related field • 3+ years of overall experience, with 2+ years of related experience and a track record of delivering production data models • Demonstrated, hands-on data modeling experience — dimensional modeling (star/snowflake schemas), semantic layer design, and multi-dimensional data • Proven ability to learn and apply business context and reflect it accurately in the resulting model • Experience working within a medallion (bronze/silver/gold) architecture, particularly building analytics-ready models from a curated gold layer • Hands-on proficiency with AWS, advanced SQL, Python, PySpark, Airflow, and Apache Spark • Experience building reporting logic, data aggregations, and API-based data retrieval for a variety of business use cases • Advanced SQL skills, including complex joins, window functions, and query optimization for large, multidimensional datasets • Deep understanding of data modeling fundamentals — sufficient to direct AI tools with informed prompts and critically evaluate output for correctness and business accuracy