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Data Modeling Director Jobs in Indiana (NOW HIRING)

POLYWOOD

Director | Data Engineering

Syracuse, IN · On-site

... ready data modeling layers with clear standards and naming conventions. • Build and maintain ... • Experience with Direct-to-Consumer and commerce analytics environments. • Experience ...

Circle K

Senior Manager Data Architecture

Columbus, IN · On-site

$62.50 - $83.75/hr

... without direct ownership, balancing standardization with team autonomy. 2. Architecture & Design * Establish and govern standards for data modeling, integration, storage, and governance across ...

Lasting Change, Inc

Fabric Data Engineer

Fort Wayne, IN · On-site

$104K - $125K/yr

... direct supervision. 2. Interact professionally with other employees, customers, and clients. 3. ... Develop analytical and dimensional data models optimized for reporting and self-service analytics.

Lasting Change Inc

Fabric Data Engineer

Fort Wayne, IN

$104K - $125K/yr

... direct supervision. 2. Interact professionally with other employees, customers, and clients. 3. ... Develop analytical and dimensional data models optimized for reporting and self-service analytics.

Pwc

AI & GenAI Data Scientist - Manager

Indianapolis, IN · On-site

$99K - $232K/yr

... models to be useful and scalable. You will also identify opportunities that contribute to the ... At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship ...

Deloitte

AI and Data Science Engineer III

Indianapolis, IN · On-site

$109K - $131K/yr

Apply economic and statistical reasoning to interpret workforce trends, model scenarios, and ... direct experience in client-facing or consulting environments. * 4+ years of demonstrated ...

Pwc

Data Engineer - Senior Manager

Indianapolis, IN · On-site

$124K - $280K/yr

Direct the team through complexity, demonstrating composure through ambiguous, challenging and ... Model and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit ...

Deckers

Director, Data Platforms & Engineering Location: United States (Remote) Interested applicants must ... Lead the design and delivery of analytics-ready data models and transformation layers using dbt as ...

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Data Modeling Director information

What is the difference between Data Modeling Director vs Data Warehouse Manager?

AspectData Modeling DirectorData Warehouse Manager
Primary FocusDesigning and overseeing data models and architectureManaging data warehouse operations and data integration
Required SkillsData modeling, database design, leadershipData warehousing, ETL processes, team management
Work EnvironmentStrategic planning, collaboration with data architectsOperational management, technical troubleshooting
Industry UsageUsed across industries with large data needsPrimarily in organizations with extensive data warehousing needs

The Data Modeling Director focuses on creating and maintaining data models and architecture, ensuring data consistency and quality. In contrast, the Data Warehouse Manager handles the day-to-day operations of data warehouses, including data integration and performance optimization. Both roles require strong technical skills, but their responsibilities differ in scope and focus.

What does a Data Modeling Director do?

A Data Modeling Director oversees the design, development, and management of data models that support an organization's data strategy and business goals. They lead teams of data modelers and analysts to create, optimize, and maintain logical and physical data models for databases, data warehouses, and other data systems. Their responsibilities include ensuring data quality, consistency, and compliance with industry standards, as well as collaborating with stakeholders to align data structures with business needs. Additionally, they often provide guidance on best practices and emerging trends in data modeling to ensure scalable and efficient data architectures.

What are the 4 types of data modeling?

Data Modeling Directors typically work with four main types of data modeling: conceptual, logical, physical, and dimensional. Conceptual models define high-level data structures, logical models specify detailed data relationships, physical models focus on how data is stored in databases, and dimensional models are used in data warehousing for analysis. Understanding these types helps in designing effective data architectures and supporting data-driven decision-making.

What is the highest paying job in data analytics?

In data analytics, senior roles such as Data Science Director or Chief Data Officer typically have the highest salaries, often exceeding six figures annually. These positions require advanced skills in data modeling, leadership, and strategic decision-making, and may involve managing large teams and complex projects.

What is the highest paid job in data science?

In data science, senior roles such as Chief Data Officer or Director of Data Science tend to have the highest salaries, often exceeding $150,000 annually, especially in large organizations. These roles require advanced skills in machine learning, data architecture, and leadership, and often involve strategic decision-making and cross-functional collaboration.

What are the key skills and qualifications needed to thrive as a Data Modeling Director, and why are they important?

To excel as a Data Modeling Director, you need deep expertise in data architecture, data modeling methodologies (such as relational, dimensional, and NoSQL), and a strong background in computer science or a related field. Experience with data modeling tools (e.g., ERwin, PowerDesigner), database systems (SQL, Oracle, MongoDB), and relevant certifications like CDMP are highly valuable. Strong leadership, communication, and project management skills set standout professionals apart by enabling effective team collaboration and stakeholder engagement. These competencies ensure the design and management of robust, scalable data structures that support organizational objectives and informed decision-making.

What is the difference between a data engineer and a data modeler?

A Data Modeling Director oversees the design and structure of data models that define how data is stored and related, focusing on creating efficient schemas and standards. A data engineer builds and maintains data pipelines, integrating data from various sources and ensuring data availability for analysis, often using tools like SQL, Python, and cloud platforms. Both roles require strong technical skills but focus on different aspects of data management.

What are some common challenges faced by a Data Modeling Director when managing cross-functional teams?

As a Data Modeling Director, a key challenge is ensuring alignment across cross-functional teams such as data engineering, business analytics, and IT. Different teams may have varying priorities, technical backgrounds, and understandings of data requirements, which can lead to miscommunication or conflicting objectives. To address this, the director must foster clear communication, establish standardized data modeling practices, and facilitate regular collaboration to ensure that data models meet both technical and business needs. Balancing technical accuracy with business relevance is essential for successful project outcomes.
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What job categories do people searching Data Modeling Director jobs in Indiana look for? The top searched job categories for Data Modeling Director jobs in Indiana are:
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Data Modeling Director jobs near you
Director | Data Engineering

Director | Data Engineering

POLYWOOD

Syracuse, IN • On-site

Full-time

Posted yesterday

Be an early applicant

Polywood rating

5.2

Company rating: 5.2 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

39th of 46 rated furniture manufacturers

Job description

Description:


HELP BUILD THE DATA FOUNDATION THAT POWERS SMARTER DECISIONS.

POLYWOOD® is looking for a Director of Data Engineering who thrives in a hands-on leadership environment and enjoys building scalable enterprise data platforms. This role is perfect for someone who loves designing architecture, establishing governance, and transforming raw ingestion pipelines into a structured, reliable Databricks lakehouse that powers enterprise reporting, operational analytics, and Direct-to-Consumer performance measurement.



What You’ll Do:

• Design and implement a scalable lakehouse medallion architecture within Databricks.

• Establish ingestion, canonical, and business-ready data modeling layers with clear standards and naming conventions.

• Build and maintain structured, governed fact and dimension models for enterprise reporting.

• Oversee ingestion pipelines using Fivetran, Airbyte, and custom integrations while optimizing cost and performance.

• Develop and manage SQL and Python transformation jobs including incremental processing, upsert logic, and snapshot modeling.

• Implement orchestration, monitoring, data quality validation, and failure recovery processes.

• Define enterprise data governance standards including access controls and reconciliation processes.

• Integrate ERP, Shopify, GA4, Google Ads, Meta Ads, and catalog marketing data into unified customer and order models.

• Lead and mentor a small team of data and analytics engineers while setting coding and review standards.

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What You Bring:

• 7+ years of experience in data engineering, analytics engineering, or data architecture.

• 3+ years leading data platform or warehouse initiatives.

• Expert-level expertise in Databricks and medallion architecture design.

• Advanced SQL proficiency and strong Python experience for data transformations.

• Experience designing fact/dimension models and implementing incremental pipelines and snapshot logic.

• Strong understanding of data governance, access control, and quality frameworks.

• Experience integrating commerce, finance, ERP, and marketing data sources into structured models.

• Strong communication skills and the ability to collaborate across technical and business teams.

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Bonus Skills:

• Experience with Direct-to-Consumer and commerce analytics environments.

• Experience optimizing pipeline cost and performance within cloud data platforms.

• Experience formalizing enterprise metric definitions across finance and operations.

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Why You’ll Love Working With Us:

• Valued Contribution: Build the foundational data infrastructure that powers enterprise decisions.

• Growth Opportunities: Shape standards, architecture, and long-term data strategy.

• Team Environment: Partner with business leaders and analytics teams to deliver trusted insights.

• Purpose Driven Work: Enable scalable analytics that strengthen operations, finance, and commerce performance.

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About Us

At POLYWOOD®, we design and build outdoor furniture that brings people together and stands the test of time. We do this using sustainable materials like our genuine POLYWOOD® lumber made from recycled plastics. But the strength of our products starts with the strength of our systems and our people.
This role plays an important part in operationalizing our Databricks investment by building a cohesive, governed, and scalable enterprise data warehouse. By establishing reliable ingestion, transformation, and modeling standards, you help ensure our organization can make confident, data-driven decisions at scale.


Check out this video - Genuine Polywood
If this sounds like the kind of impact you want to make, we’d love to meet you! Apply today!

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POLYWOOD is an equal opportunity employer. POLYWOOD evaluates qualified applicants without regard to characteristics protected by federal, state, or local laws. #ZR

Requirements:


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