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Data Modeling Director Jobs in Gary, IN (NOW HIRING)

Data modeling and architecture: Own data modeling standards across REMS - including relational ... Please direct any other general recruiting inquiries to our Contact Us page > I want to work for ...

Senior Data Engineer

Chicago, IL · On-site

$65 - $80/hr

Develop source-to-target mappings for the canonical marketing data model. * Translate identity ... We pride ourselves on offering medical, dental, 401(k), direct deposit and commuter benefits to our ...

Collaborate with the Data Architect to align platform implementation with enterprise data models ... A minimum of 2 years of experience managing or leading a team of data engineers, including direct ...

Collaborate with the Data Architect to align platform implementation with enterprise data models ... A minimum of 2 years of experience managing or leading a team of data engineers, including direct ...

Data Architect, Next Platform

Chicago, IL · On-site +1

$150K - $200K/yr

Direct experience working with EHR, OMOP, DICOM, genomic data models, or longitudinal patient records. #LI-BL1 Chi: $140,000-$190,000 NYC/SF: $150,000-$200,000 The expected salary range above is ...

Data Architect, Next Platform

Chicago, IL · On-site

$150K - $200K/yr

Direct experience working with EHR, OMOP, DICOM, genomic data models, or longitudinal patient records. #LI-BL1 Chi: $140,000-$190,000 NYC/SF: $150,000-$200,000 The expected salary range above is ...

Knowledge of statistical methods and basic predictive modeling techniques. What We Offer * Targeted Placement: Direct marketing to our network of hiring managers in the Data, Technology, and Business ...

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Data Modeling Director information

See Gary, IN salary details

$51.7K

$127.9K

$199K

How much do data modeling director jobs pay per year?

As of Aug 29, 2026, the average yearly pay for data modeling director in Gary, IN is $127,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,500.00 and $162,700.00 per year, depending on experience, location, and employer.

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 key skills and qualifications needed to thrive as a Data Modeling Director?

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 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.

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 are the most commonly searched types of Data Modeling jobs in Gary, IN?

The most popular types of Data Modeling jobs in Gary, IN are:

What are popular job titles related to Data Modeling Director jobs in Gary, IN?

For Data Modeling Director jobs in Gary, IN, the most frequently searched job titles are:

What job categories do people searching Data Modeling Director jobs in Gary, IN look for?

The top searched job categories for Data Modeling Director jobs in Gary, IN are:

Sr. Director, Data Engineering

JLL

Chicago, IL

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago


JLL rating

8.3

Company rating: 8.3 out of 10

Based on 289 frontline employees who took The Breakroom Quiz

47th of 206 rated real estate companies


Job description

JLL empowers you to shape a brighter way.

Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented peopleand empowering them tothrive, grow meaningful careers and to find a place where they belong. Whether you've got deep experience in commercial real estate, skilled trades or technology, or you're looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.

Sr. Director, Data Engineering (REMS)

About JLL and JLL Technologies

JLL is a leading professional services firm that specializes in real estate and investment management. Our vision is to reimagine the world of real estate, creating rewarding opportunities and amazing spaces where people can achieve their ambitions. In doing so, we will build a better tomorrow for our clients, our people, and our communities.

JLL Technologies is a specialized group within JLL. At JLL Technologies, our mission is to bring technological innovation to commercial real estate. We deliver unparalleled digital advisory, implementation, and services solutions to organizations globally. Our goal is to leverage technology to increase the value and liquidity of the world's buildings, while enhancing the productivity and happiness of those that occupy them.

What this job involves

We are seeking an experienced Sr. Director, Data Engineering to lead the REMS (Real Estate Management Services) Data Engineering team within JLL Technologies. In this role, you will own people leadership, delivery, and technical direction for the data platforms and pipelines that power REMS products across JLL's global real estate management operations - spanning property and lease data, facilities workflows, work order management, and operational intelligence.

You will set priorities in close partnership with REMS Product and Engineering leadership, govern the technical roadmap, grow a high-performing team, and ensure the delivery of reliable, well-governed data assets that scale with the business. The scope spans platform strategy, data architecture, team development, and stakeholder alignment across REMS and enterprise data functions.

The ideal candidate blends Principal Data Engineer-level technical credibility - expert data engineering, cloud architecture, and cross-domain platform delivery - with proven experience managing through leads and managers, navigating complex enterprise environments, and translating real estate management data challenges into durable engineering capabilities.

Location: Chicago or Dallas

Travel 20%

What you'll get to do

As Director of Data Engineering for REMS, your "customers" include REMS Product leadership, application and platform engineering teams, facilities and property operations practitioners who depend on accurate and timely data, and enterprise data consumers across JLL. Your mission is to lead the REMS Data Engineering function - defining the roadmap, operating model, team structure, and engineering standards that turn complex real estate management data into trusted, scalable platform capabilities.

This is an opportunity to shape how data engineering enables the next generation of REMS products - from intelligent property workflows and lease analytics to data-driven operational automation - while building the engineering culture, governance practices, and technical foundations that make that platform sustainable and trusted across JLL.

Key responsibilities

Strategic architecture and vision: Define and drive the REMS data platform strategy, consolidating fragmented data sources and legacy pipelines into a unified, governed, and scalable architecture that serves as the foundation for analytics, AI, and operational decision-making across real estate management.

Technical leadership: Provide hands-on technical leadership across the REMS Data Engineering team and related initiatives - setting architectural standards, design patterns, and engineering best practices that raise the quality bar across the organization and ensure alignment with enterprise platform standards.

Data platform delivery: Oversee the design, delivery, and continuous improvement of REMS data pipelines, APIs, and backend data services that ingest, transform, and serve property, lease, facilities, and operational data to downstream products, analytics, and AI systems.

Data modeling and architecture: Own data modeling standards across REMS - including relational, dimensional, and NoSQL schemas - ensuring data structures are designed for performance, maintainability, and reliable consumption by business intelligence, data science, and application teams.

Data governance and quality: Establish DataOps practices, data quality frameworks, lineage tracking, and compliance controls that ensure REMS data products are production-ready, auditable, and trusted - with clear ownership models and monitoring across all data assets.

Enterprise integration and API strategy: Architect integration patterns and API strategies that enable seamless data access across REMS applications, analytics platforms, and enterprise systems - including event-driven patterns and consumption standards for both internal and external data consumers.

Cross-functional leadership: Partner with REMS Product, Application Engineering, Enterprise Data, and business stakeholders to align data platform capabilities with product strategy and operational priorities - translating complex data challenges into actionable roadmaps with measurable outcomes.

Team development and mentorship: Hire, develop, and retain data engineers and team leads across all levels; conduct architecture and delivery reviews, provide technical guidance, and build a team culture defined by ownership, curiosity, and continuous improvement.

Stakeholder management: Serve as the data engineering voice in product reviews, architecture forums, and executive presentations - communicating roadmap, trade-offs, and technical direction with clarity and confidence to both technical and business audiences.

Who you are

You are a people leader who still speaks fluent data engineering - pipelines, platforms, data models, and the unglamorous work of making real estate management data trustworthy at scale. You are genuinely curious about the "why" and the "what" behind every data problem, not just the "how," and you bring that curiosity into discovery conversations with REMS product and operations stakeholders before ever reaching for a technical solution. You are as comfortable in an architecture review with senior engineers as you are in a roadmap discussion with product executives, and you build trust in both rooms by listening well and delivering reliably. You create clarity for your team when priorities compete, and you develop managers and engineers who grow in scope, confidence, and impact.

Required qualifications

  • People management: 5+ years of people management experience, including at least 1-2 years managing managers or team leads - not just ICs - with accountability for performance, staffing, delivery outcomes, and team development across multiple scrum teams.

  • 10+ years of data engineering experience across multiple large, complex projects and technology domains.

  • Expert proficiency in Python and SQL; strong distributed data processing experience with PySpark/Spark; demonstrated ability to architect complex end-to-end data solutions.

  • 5+ years hands-on with cloud platforms (Azure or AWS), including advanced data services such as Databricks, Azure Data Factory, Synapse, AWS Glue, or Redshift.

  • Proven data modeling expertise across relational, dimensional, and NoSQL schemas (CosmosDB, MongoDB, PostgreSQL); experience designing data structures that balance performance, scalability, and analytical consumption.

  • Demonstrated experience establishing data governance frameworks in a production enterprise environment - data quality standards, lineage tracking, ownership models, and compliance controls.

  • Experience orchestrating multiple data engineering project teams simultaneously; track record of shaping organizational data strategy and aligning engineering priorities with business outcomes.

  • Exceptional communication and stakeholder management skills - able to earn trust quickly, drive alignment across product and engineering, and present technical trade-offs clearly to executive audiences.

Preferred qualifications

  • Experience leading data engineering for a real estate, facilities, lease management, or asset-intensive operational domain.

  • Familiarity with REMS or related property management platforms (e.g., MRI, Yardi, IBM Maximo, ServiceNow FM).

  • Hands-on experience with agentic AI, RAG architectures, vector databases, or MCP integrations for building AI-ready data foundations.

  • Experience with data orchestration tools such as Airflow, Prefect, or dbt for managing complex pipeline dependencies and transformations.

  • Strong DevOps and DataOps practices - CI/CD pipeline design, containerization (Docker, Kubernetes), infrastructure-as-code (Terraform or CloudFormation), and observability tooling.

  • Experience with data governance compliance standards (GDPR, CCPA, data residency requirements) and enterprise security practices for sensitive data.

  • Master's degree in Computer Science, Engineering, Data Science, or a related field.

Key attributes

Leadership: Builds and retains strong teams through leads and managers; delegates effectively while staying close to critical technical risks and maintaining the engineering credibility that earns team respect.

Stakeholder Partnership: Navigates REMS product and enterprise priorities with poise; negotiates scope and timelines with data-driven rationale and a consistent bias toward shared outcomes.

Judgment: Makes sound trade-offs among quality, speed, cost, and risk - especially in domains where data accuracy has direct operational, financial, or contractual consequences.

Communication: Explains technical architecture and platform trade-offs clearly to executives and product partners; listens actively for the business constraints that should shape engineering decisions.

Ownership: Accountable for team outcomes, platform health, and the continuous improvement of engineering practices - not just delivery milestones.

This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship.

Estimated compensation for this position:

229,000.00 - 309,000.00 USD per year

This range is an estimate and actual compensation may differ. Final compensation packages are determined by various considerations including but not limited to candidate qualifications, location, market conditions, and internal considerations.

Location:

On-site -Chicago, IL, Dallas, TX

If this job description resonates with you, we encourage you to apply, even if you don't meet all the requirements. We're interested in getting to know you and what you bring to the table!


Personalized benefits that support personal well-being and growth:

JLL recognizes the impact that the workplace can have on your wellness, so we offer a supportive culture and comprehensive benefits package that prioritizes mental, physical and emotional health. Some of these benefits may include:

  • 401(k) plan with matching company contributions

  • Comprehensive Medical, Dental & Vision Care

  • Paid parental leave at 100% of salary

  • Paid Time Off and Company Holidays

  • Early access to earned wages through Daily Pay

At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you'repursuing.

JLL Privacy Notice

Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect the personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL's recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely.

For more information about how JLL processes your personal data, please view our Candidate Privacy Statement.

For additional details please see our career site pages for each country.

For candidates in the United States, please see a full copy of our Equal Employment Opportunity policy here.

Jones Lang LaSalle ("JLL") is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process - including the online application and/or overall selection process - you may email us at HRSCLeaves@jll.com. This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL.

Pursuant to the Arizona Civil Rights Act, criminal convictions are not an absolute bar to employment.

Pursuant to Illinois Law, applicants are not obligated to disclose sealed or expunged records of conviction or arrest.

Pursuant to Columbia, SC ordinance, this position is subject to a background check for any convictions directly related to its duties and responsibilities. Only job-re...


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