Main image of article Data Modeler: Sample Resume, Tips for Applying, and More

What is a data modeler? In simplest terms, a data modeler is a tech pro who organizes their organization’s databases in ways that are optimal for data scientists, software developers, business intelligence analysts, and others who rely on that data to do their daily tasks.

The job involves a good deal of engineering and data architecture know-how, along with the ability to work with other stakeholders within an organization’s data operations, including (but not limited to) data engineers, data analysts, and data scientists. We’ll explore the nuances of the data modeler role, and offer up a resume template you can use when applying for data modeling jobs.

What does a data modeler do on a day-to-day basis?

On a strategic level, a good data modeler:

  • Has analyzed and understood how data moves through their organization, from its initial intake to when data scientists and others use it for analytics and products.
  • Understands (and perhaps has helped build) the company’s database management infrastructure.
  • Has worked with data scientists, executives, and others throughout the organization to determine how data will be used (especially with regard to any end-users), database safeguards, data dictionaries, and other strategic issues.

On a day-to-day basis, that means a data modeler might do any of the following:

  • Define and analyze the data requirements for a particular project or data process.
  • Standardize current data practices, such as software developers’ use of databases for product development.
  • Collaborate on data models and idealized data flows (this often involves input from an organization’s data scientists and data engineers).
  • Troubleshooting errors in the organization’s data systems.
  • Iterating and improving on the current data systems.

As with other data-centric roles, a data modeler will need to possess a core set of technical skills if they want to effectively design and implement an organization’s data strategy, including:

Data modeler is also a job with a heavy “soft skills” component; those who excel in the role are very good at empathy, communication, and other skills needed to work with stakeholders throughout an organization. As you put together a resume (and move into the job interview stage), you’ll need to emphasize both your technical and soft skills in the context of your previous jobs; if you can show that you utilized a broad portfolio of abilities to overcome challenges, design and implement effective data infrastructures, and complete projects, you’ll have a better chance of landing the position.

With all that in mind:

Data Modeler Sample Resume

As with resumes for other tech professional positions, the goal with a data modeler resume is to show how your previous experience and skills make you the best possible candidate for the offered role. Before writing your resume, re-examine the original job posting; note the skills. Make sure to list any of those skills you’ve mastered in your own resume and cover letter, as automated resume scanners (used by many organizations) are designed to scan for them… and weed out applications that mention too few.

With that in mind, here’s a sample data modeler resume you can use to customize your own:

 

Thomas Song tsong@email.com 000.555.1212 123 Any St. Omaha, Neb. 00000 Willing to Relocate

Data Modeler

Offering a proven track record of supporting and influencing positive outcomes in business units and companies throughout the financial services industry through the application of cutting-edge tools and creation of detailed, production-level technical specifications, as well as intuitive conceptual, logical, relational and physical data models. Enthusiastic learner and excellent problem-solver.  Willing to relocate and start work within two weeks anywhere in the U.S. without financial assistance.

  • Lowered processing costs and time by 10% for accident claims through the review and reverse engineering of existing database structures, which reduced redundancies and consolidated databases.
  • Enabled the development of two new insurance products that produced $25 million in first-year sales through the development of a cutting-edge logical data model and module enhancements that facilitated the creation of test cases and precise actuarial forecasting and analysis.
  • Empowered productivity improvements and data sharing throughout a major banking enterprise by using ERwin r7.3 for effective model management.
  • Spearheaded the design and creation of data models that boosted deposits 8% by identifying active, inactive and new investors and private banking clients, tracking their deposits and withdrawals, and providing marketing with fact and dimension tables on a daily basis. View Samples and More Accomplishments: [Insert link to online portfolio]

Data Modeler’s Tool Box

Data Modeling Tools: ERwin r7.1/7.2/7.3/8.0, Oracle Designer 12.0 and ER Studio 8.5.3. OLTP Tools: Microsoft Analysis Services, Business Objects, and Crystal Reports 9. Databases: Oracle, MS SQL Server, MS Access, DB2. Business Applications: Microsoft Office Suite, Visio. Operating Systems: Microsoft Windows 9x/NT/2000/XP/Vista/7 and UNIX. Data Warehouse: Informatica, SSIS. Modeling: Star-Schema Modeling, Snowflake Schema Modeling, Fact and Dimension tables.

Modeling Experience

Mutual of Nebraska, Data Modeler     Jan. 2012 to present A roving modeler, responsible for gathering and translating business requirements into detailed, production-level technical specifications, creating robust data models, data analysis features and enhancements for this major provider of life and accident insurance. Successfully completed more than 22 projects that produced 10% gains in productivity, $25 million in revenues and 2% in profits. Related Tasks, Responsibilities and Actions:

  • Collaborate with data architects for data model management and version control.
  • Conduct data model reviews with project team members.
  • Capture technical metadata through data modeling tools.
  • Create data objects (DDL).
  • Enforce standards and best practices around data modeling efforts.
  • Ensure data warehouse and data mart designs efficiently support BI and end user
  • Collaborate with BI teams to create reporting data structures.

MidWest Bank, Data Modeler     2010 to 2012 Promoted into a data modeling role handling multiple projects for home loans, auto finance and private banking for this major bank after serving as a marketing data analyst for just two months. Empowered the retention and acquisition of private banking customers, which boosted deposits by 8%. Increased productivity and reduced loan processing time 2% by facilitating the sharing of data among home loans, auto loans and credit cards. Related Tasks, Responsibilities and Actions:

  • Extracted data from Oracle and SQL Server and DB2 using Informatica to load it into a single data warehouse repository.
  • Created entity relationship diagrams and multidimensional data models, reports and diagrams for marketing.
  • Used Model Mart of ERwin for effective model management of sharing, dividing and reusing model information and design for productivity improvement.
  • Developed and implemented measurements for various marketing campaigns.
  • Created a net loss model which analyzes the impact of loan defaults and recoveries.
  • Created a relational model and dimensional model for online services such as online banking and automated bill pay.
  • Applied data cleansing/data scrubbing techniques to ensure consistency amongst data sets.
  • Developed logical data models and physical data models using ER-Studio.

Close the Gap, Data Analyst     2008 to 2010 Acquired training and expertise in data modeling while serving as a data analyst for this major provider of supplemental accident insurance. Related Tasks, Responsibilities and Actions:

  • Created and implemented ER models and dimensional models (star schemas).
  • Generated SQL scripts.
  • Assisted DBA's in the development of physical database.

Major Holdings, DBA     2005 to 2008

Education and Training

  • Master's Degree in Information Systems, University of Phoenix
  • Bachelor’s Degree in Information Technology, University of Nebraska College of Information Science and Technology
  • Data Modeling Concepts
  • Data Modeling with CA ERwin® Data Modeler
  • Process Modeling with CA ERwin® Process Modeler
  • Model Management with CA ERwin® Data Modeler, Process Modeler and Model Manager
  • Steve Hoberman, Donna Burbank, & Chris Bradley. Data Modeling for the Business.

Thomas Song ♦ LinkedIn ♦ Portfolio ♦ Facebook ♦ 000.555.1212 ♦ tsong@email.com