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Data Quality Developer Jobs in Oklahoma (NOW HIRING)

Identify and document data quality issues; recommend data cleansing, transformation, or enrichment ... Partner with stakeholders, data stewards, and engineers to identify and implement data cleansing ...

Identify and document data quality issues; recommend data cleansing, transformation, or enrichment ... Partner with stakeholders, data stewards, and engineers to identify and implement data cleansing ...

Your Job Koch Engineered Solutions is seeking a Data Product Analyst for the ET&S data delivery team. The role sits at the intersection of governance, data quality, and product delivery. It ...

Data Engineer II

Tulsa, OK · On-site

$120/hr

Data Engineer II/III Location: Tulsa, Oklahoma Salary: $120-135k Position is not eligible for ... Create automated data quality monitoring, validation, and alerting processes. * Develop and publish ...

Data Engineer

Oklahoma City, OK · On-site

$106K - $127K/yr

Supporting data quality, governance, and documentation best practices * Troubleshooting pipeline ... engineering, data warehousing, or ELT development * Hands-on experience with Snowflake and ...

Data Engineer

Oklahoma City, OK · On-site

$106K - $127K/yr

Supporting data quality, governance, and documentation best practices * Troubleshooting pipeline ... engineering, data warehousing, or ELT development * Hands-on experience with Snowflake and ...

Data Engineer

Oklahoma City, OK · On-site

$106K - $127K/yr

Supporting data quality, governance, and documentation best practices * Troubleshooting pipeline ... engineering, data warehousing, or ELT development * Hands-on experience with Snowflake and ...

You will recommend enterprise-level data quality measures and requirements, monitor data quality trends, define SLAs, and work with data engineers and data producers to resolve and prevent data ...

You will recommend enterprise-level data quality measures and requirements, monitor data quality trends, define SLAs, and work with data engineers and data producers to resolve and prevent data ...

You will recommend enterprise-level data quality measures and requirements, monitor data quality trends, define SLAs, and work with data engineers and data producers to resolve and prevent data ...

Lead Data Engineer

Oklahoma City, OK

$106K - $127K/yr

... asset quality, and peer groups) Handle schema drift, data quality, and reconciliation; make ... engineering to deliver governed, queryable data products KPIs Data freshness and pipeline ...

Lead Data Engineer

Oklahoma City, OK

$106K - $127K/yr

... asset quality, and peer groups) Handle schema drift, data quality, and reconciliation; make ... engineering to deliver governed, queryable data products KPIs Data freshness and pipeline ...

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Data Quality Developer information

What is a data quality developer?

A Data Quality Developer is an IT professional responsible for ensuring the accuracy, consistency, and reliability of data within an organization’s systems. They design and implement processes, tools, and scripts to identify and resolve data quality issues such as duplicates, missing values, or inconsistencies. Their role often involves collaborating with data engineers, analysts, and business stakeholders to define data quality requirements and standards. Additionally, Data Quality Developers monitor data pipelines, perform data profiling, and create automated tests to maintain high data integrity over time.

What are the key skills and qualifications needed to thrive as a data quality developer?

A Data Quality Developer should have strong skills in data analysis, database management, and data profiling, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, SQL, data quality platforms (like Informatica or Talend), and relevant certifications are often required. Attention to detail, problem-solving, and effective communication are crucial soft skills for collaborating with diverse teams and resolving data issues. These abilities ensure the delivery of accurate, reliable data that supports business decision-making and operational efficiency.

What are some common challenges data quality developers face when working with large datasets, and how can they overcome them?

Data Quality Developers often encounter challenges such as inconsistent data formats, missing values, and integration issues when working with large datasets from multiple sources. To overcome these, they typically implement automated validation rules, build robust data profiling scripts, and work closely with data engineers and business analysts to understand data requirements. Regular communication with stakeholders and adopting best practices for data governance can also help ensure data accuracy and reliability across the organization.

What is the difference between Data Quality Developer vs Data Analyst?

AspectData Quality DeveloperData Analyst
Primary FocusEnsuring data accuracy, consistency, and integrity through data quality processes and toolsAnalyzing data to identify trends, generate reports, and support decision-making
Skills & CertificationsData management, SQL, data profiling, data governance certificationsData analysis, SQL, Excel, visualization tools, statistical knowledge
Work EnvironmentData management teams, IT departments, data warehousesBusiness units, marketing, finance, operations
Common UsageFocuses on data quality standards and improvementsFocuses on data insights and reporting

While both roles work with data, Data Quality Developers concentrate on maintaining high data standards and integrity, whereas Data Analysts interpret data to support business decisions. Understanding these differences helps organizations assign the right responsibilities and skills to each role.

Data Quality Analyst I

Tulsa, OK • On-site

QuikTrip
Retail • 5 - 10K employees

Full-time

Posted 12 days ago


QuikTrip rating

7.0

Company rating: 7.0 out of 10

Based on 645 frontline employees who took The Breakroom Quiz


Job description

Primary Purpose of job:
This position is responsible for profiling, analyzing, and evaluating data from QuikTrip's source systems to support data governance and Master Data Management (MDM) efforts, ensuring data used in centralized master data systems is accurate, complete, consistent, relevant, valid, and trustworthy. This position relies on instructions and pre-established guidelines to perform the functions of the job.
Major Functions:
Data Profiling - 40%
a. Utilize profiling tools to analyze source data from QuikTrip systems.
i. Base profiling: structure and constraint (primary/foreign key), duplicate, obsolete and invalid record, and composite analyses.
ii. Column-level profiling: identifying missing or non-standard values, data types, and allowed values.
iii. Cross-column profiling: dependency checks and business rule validations.
iv. Cross-table and cross-system profiling: join analysis to identify anomalies such as duplications and orphans, and attribute survivorship.
b. Document and maintain data definitions and data types in a data dictionary.
c. Adhere to QuikTrip's data governance standards and best practices.
2. Quality Analysis - 30%
a. Analyze profiling results against the key dimensions of data quality: accuracy, completeness, consistency, timeliness, relevance, validity, and uniqueness.
b. Identify and document data quality issues; recommend data cleansing, transformation, or enrichment strategies.
c. Create metrics and reports on data quality to track improvements; report results to management.
d. Partner with stakeholders, data stewards, and engineers to identify and implement data cleansing rules.
e. Create and manage test plans for user acceptance testing.
3. Application Administration - 10%
a. Perform the administration of Data Governance specific applications like Data Catalog, MDM Hubs, stewardship tools, etc.
b. Includes system configuration, user access management, troubleshooting, and ongoing platform maintenance to support business operations.
4. Documentation - 10%
a. Partner with business stakeholders and subject matter experts to identify and document scope, purpose, business rules, and requirements.
b. Document lifecycle management processes for data creation, modification, and deletion.
c. Identify and document data sources, including systems, files, and tables.
d. Translate business rules, processes, and requirements into functional and non-functional requirements.
e. Understand source systems contributing to the master data domain and identify overlaps and inconsistencies across systems.
5. Training - 5%
a. Seek input from team members and supervisors on areas to improve skill set.
b. Actively apply feedback received into day-to-day work and strive to improve performance.
c. Actively utilize training outlets as necessary to improve analytical and technical skills, including self-study, in-house classes, seminars, or online training.
d. Maintain professional and technical knowledge by attending ongoing training, reviewing professional publications, and reviewing industry best practices and new technologies to determine fit within the organization.
6. Administration and Communication - 5%
a. Listen to others and accept input from team members.
b. Clearly articulate ideas and thoughts both in verbal and written formats.
c. Accurately prepare written business correspondence that is coherent, grammatically correct, effective, and professional.
d. Timely communicate status updates with supervisors, project stakeholders, and/or key customers regarding specific assignments and overall scheduling and coordination needs.
Position in Organization:
Reports to: Manager of Enterprise Data & Business Intelligence
Relationships:
Inside the Company: Enterprise Data & Business Intelligence staff, business stakeholders, data stewards, and primary users of data across departments.
Outside the Company: N/A
Position Specifications:
The required specifications (education, experience, and skills) are those that the employee must have to hold the position. Applicants applying for this position must possess the required specifications in order to be considered for the job. The desired specifications are those that are not required for the employee to hold the position, but the employee should try to obtain the desired education, experience, and/or skills to be effective and successful in the position.
Required education: Bachelor's degree in mathematics, computer science, statistics, or a related field, or equivalent professional experience.
Desired education: Coursework or certification in data management, data quality, or data governance (such as CDMP).
Required experience: 3 or more years of professional experience working with real-world datasets, or meets desired education requirements above.
Desired experience: Experience supporting Master Data Management (MDM) or data quality initiatives in a business environment.
Required skills: Proficiency with SQL; understanding of database systems and querying languages used at QuikTrip.
Desired skills: Python; experience with Databricks or similar cloud data platforms; ability to create clear, insightful data visualizations using Power BI or Excel.
Additional criteria: This position requires good communication skills to work effectively with business stakeholders and data stewards across the organization. Ability to work in a fast-paced team environment. Works under general supervision. Intermittent or extended travel may be required based on project requirements.
Starting Salary: $74,900 - $93,630
Benefits: Employee Benefits - QuikTrip
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