data engineer iii

SiriusXM

Responsibilities: 
Data Engineer III - (employer: Sirius XM Radio LLC; job location: Irving, TX) - Architect, build, automate, and launch scalable data pipelines that support marketing growth efforts. Build integrations and ETL processes with 3rd party data to automatically pull data from external sources into operational and analytical data pipelines. Use SQL and Python to write production-quality code to meet data transformation needs of analysts, data scientists and other business partners. Streamline and automate tasks, and innovate by building reusable components that can be used across multiple use cases and by the marketing analytics team in Google Cloud Platform. Visualize, communicate and present statistical model outputs and analysis to various technical and non-technical stakeholders. Develop automated and ad hoc reports, dashboards and models to guide business decisions. Requirements: Bachelor’s degree in Computer Science, Computer Engineering, or Big Data Analytics and Information Technology, plus 2 years of experience in the position offered or another data engineer position. All of the required experience must have included developing scalable ETL processes using SQL and Python coding, data warehouse architecture and data modeling; creating and maintaining production dashboards in Tableau or Zeppelin; applying statistical modeling concepts and techniques including statistical regression and A/B testing; performing marketing analytics; and using or working with the following tools/technologies: Airflow, Linux, R, Apache Spark, and cloud-based platforms (such as GCP or AWS). #LI-DNI. This role entails hybrid work, with time split between working in our Irving, TX office and flexibility to telecommute from another U.S. location. Apply online at www.siriusxm.com/careers. P-2026-576.

Data Engineer III

adswizz

<ul><li>Irving, Texas</li><li>
Regular Employee Full-Time</li><li>
P-2026-576</li></ul>
 <div><div>Data Engineer III - (employer: Sirius XM Radio LLC; job location: Irving, TX) - Architect, build, automate, and launch scalable data pipelines that support marketing growth efforts. Build integrations and ETL processes with 3rd party data to automatically pull data from external sources into operational and analytical data pipelines. Use SQL and Python to write production-quality code to meet data transformation needs of analysts, data scientists and other business partners. Streamline and automate tasks, and innovate by building reusable components that can be used across multiple use cases and by the marketing analytics team in Google Cloud Platform. Visualize, communicate and present statistical model outputs and analysis to various technical and non-technical stakeholders. Develop automated and ad hoc reports, dashboards and models to guide business decisions. Requirements: Bachelor&rsquo;s degree in Computer Science, Computer Engineering, or Big Data Analytics and Information Technology, plus 2 years of experience in the position offered or another data engineer position. All of the required experience must have included developing scalable ETL processes using SQL and Python coding, data warehouse architecture and data modeling; creating and maintaining production dashboards in Tableau or Zeppelin; applying statistical modeling concepts and techniques including statistical regression and A/B testing; performing marketing analytics; and using or working with the following tools/technologies: Airflow, Linux, R, Apache Spark, and cloud-based platforms (such as GCP or AWS). #LI-DNI. This role entails hybrid work, with time split between working in our Irving, TX office and flexibility to telecommute from another U.S. location. Apply online at www.siriusxm.com/careers. P-2026-576.</div>
P-2026-576</div>

Hanger

<div><div>The Data Engineer III is a senior-level technical contributor responsible for designing, developing, and maintaining scalable data solutions that support enterprise analytics, reporting, and operational initiatives at Hanger. This role partners closely with business stakeholders, analytics teams, and IT to ensure reliable, secure, and high-performing data pipelines and data models.</div><div> 
</div><div>At Level III, this position operates with a high degree of autonomy, leads moderately complex initiatives, mentors junior engineers, and contributes to architectural decisions that support Hanger&rsquo;s modern data platform strategy. This role is based in Austin, TX.</div> 
<ul><li>
Design, develop, and maintain scalable data pipelines and integrations using Microsoft Azure and Microsoft Fabric.</li><li>
Build and optimize ETL/ELT processes to ingest structured and semi-structured data from internal and external systems.
</li><li>Design and implement logical and physical data models to support enterprise analytics, reporting, and business intelligence initiatives.
</li><li>Develop and optimize relational databases, including Microsoft SQL Server and PostgreSQL (PostgresDB).
</li><li>Apply dimensional modeling techniques (e.g., star and snowflake schemas) to support reporting and analytical use cases.
</li><li>Leverage Microsoft Azure services (e.g., Azure Data Factory, Azure Synapse, Azure SQL, Azure Storage) to deliver scalable, secure data solutions.
</li><li>Develop and maintain Microsoft Fabric solutions, including pipelines, lakehouse environments, and semantic models.
</li><li>Integrate and manage data ingestion tools such as Fivetran or similar data integration platforms.
</li><li>Monitor, troubleshoot, and optimize data pipeline performance and reliability.
</li><li>Ensure adherence to data governance, security, and compliance standards.
</li><li>Collaborate with cross-functional teams to translate business requirements into scalable technical solutions.
</li><li>Provide mentorship and technical guidance to Data Engineers I and II.
</li><li>Participate in code reviews and promote best practices in data engineering and DevOps methodologies.</li></ul> 
<ul><li>
Required:
<ul><li>5+ years of experience in data engineering, data warehousing, or related technical roles.
</li><li>Hands-on experience building and maintaining cloud-based ETL/ELT pipelines.
</li><li>Strong experience with Microsoft Azure data services.
</li><li>Demonstrated experience in data modeling for enterprise analytics.
</li><li>Advanced proficiency in SQL and experience with Microsoft SQL Server and PostgreSQL (PostgresDB).
</li></ul></li><li>Preferred:
<ul><li>Bachelor&rsquo;s degree in Computer Science, Information Systems, Engineering, or a related technical field.
</li><li>Experience with Microsoft Fabric.
</li><li>Experience with Fivetran or similar data integration platforms.
</li><li>Experience in healthcare or other regulated industries.
</li><li>Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code.</li></ul></li><li>
Must have, or be eligible to obtain, a valid driver&rsquo;s license and driving record within the standards outlined within Hanger&rsquo;s Motor Vehicle Safety Policy and Procedures.</li></ul></div>

University of Utah

<div>Details
Open Date 03/05/2026
Requisition Number PRN44413B
Job Title Data Engineers
Working Title Data Engineer III
Career Progression Track P00
Track Level P3 - Career
FLSA Code Computer Employee
Patient Sensitive Job Code? No
Standard Hours per Week 40
Full Time or Part Time? Full Time
Shift Day
Work Schedule Summary
<ul><li>Full-time, 40 hours per week. Monday &ndash; Friday from 8:00 am to 5:00 pm
</li><li>This position offers a flexible, mostly remote work schedule for candidates who reside in the state of Utah. While most duties can be performed remotely, the employee must be available to attend essential meetings and events on campus as needed.
</li><li>A hybrid telework schedule is available for this position, dependent on operational needs and management approval. The arrangement will be established in partnership with the manager and is subject to ongoing departmental needs.
</li></ul>VP Area U of U Health - Academics
Department 02228 - Data Coordinating Center
Location Campus
City Salt Lake City, UT
Type of Recruitment External Posting
Pay Rate Range 81,983 to 124,278
Close Date 06/05/2026
Priority Review Date (Note - Posting may close at any time)
Job Summary
Data Engineers
Join the Utah Data Coordinating Center ( DCC ) as a Data Engineer, where your work will directly enable innovative clinical research at the University of Utah and across national partners. You&rsquo;ll lead the design of scalable data systems, define and enforce architecture standards, and work alongside software developers, data analysts, and research teams to ensure our platforms evolve with the needs of scientific discovery. This is a growth-focused role ideal for someone who thrives in a collaborative, mission-driven environment. The Utah DCC supports large-scale health data infrastructure that underpins national emergency response, clinical registries, and federal research initiatives.
Establish project teams and provide overall direction for technical projects from initiation through to delivery. Perform project requirements, estimation, and budget management. Formulate project scope and delivery strategies and establish milestones/schedules. Maintain and report project status and monitor progress of all team members. Gather required data from end-users to evaluate objectives, goals, and scope to create technical specifications. Serve as liaison between technical and non-technical departments in order to ensure that all targets and requirements are met. Keep leadership informed of key issues that may impact project completion, budget, or other results.
As a Data Engineer, your responsibilities will include:
1. Design, develop, and maintain database architecture following industry best practices
Design and implement scalable, secure, and high-performing database solutions aligned with industry standards and architectural best practices. This includes data modeling (conceptual, logical, and physical), schema design, indexing strategies, performance tuning, backup and recovery planning, and ensuring data integrity and consistency. Establish governance standards, naming conventions, version control processes, and documentation to support maintainability, reliability, and long-term scalability across environments.
2. Build, optimize, and maintain scalable data pipelines
Design, develop, and orchestrate reliable, high-performance data pipelines from initial data ingestion through final delivery. This includes data pipeline development, orchestration, transformation logic, and supporting data models optimized for analytics and operational workloads.
3. Develop and optimize data processing and automation code
Design, implement, and maintain robust code for data extraction, transformation, integration, and analysis using appropriate languages and frameworks. Optimize performance, ensure data accuracy, and uphold high standards for code quality, reliability, and maintainability in alignment with software and data engineering best practices.
4. Drive continuous improvement and innovation in cloud data technologies ( AWS -focused)
Stay current with emerging data engineering technologies, industry trends, and evolving AWS services to continuously enhance platform capabilities and architectural standards. Evaluate and adopt appropriate AWS services (e.g., S3, Glue, Lambda, Redshift, RDS , EMR , Step Functions, Lake Formation) to improve scalability, performance, cost efficiency, and reliability. Balance innovation with operational excellence by maintaining and optimizing existing services, enforcing best practices, and ensuring stable, secure, and high-performing production environments.
5. Collaborate with business partners to develop scalable data solutions
Partner with internal teams and external stakeholders to design and deliver innovative data solutions that support evolving business needs. This includes developing and exposing data through APIs, building and maintaining multi-dimensional cubes and semantic models, enabling secure data sharing, and creating reusable data services. Translate business requirements into scalable technical solutions that align with enterprise architecture standards, governance policies, and performance expectations.
6. Implement and maintain CI/CD and version control best practices
Design, implement, and support robust CI/CD pipelines to automate build, test, deployment, and release processes for data pipelines, database objects, and cloud infrastructure. Enforce effective version control practices using Git-based workflows, including branching strategies, pull requests, code reviews, and release management. Promote automated testing, infrastructure as code (IaC), and deployment standards to ensure consistency, traceability, reliability, and rapid, low-risk delivery across environments.
7. Develop and support data pipelines for business intelligence and analytics
Design, build, and maintain reliable, scalable data pipelines that deliver curated, analytics-ready datasets to support Business Intelligence and reporting needs.
Implement transformation logic, data validation checks, and orchestration workflows to ensure accuracy, consistency, and timely data availability. Proactively monitor pipeline performance, troubleshoot data issues, and optimize data flows to support dashboards, KPI tracking, ad hoc analysis, and enterprise reporting requirements.
8. Support and implement data security and compliance requirements
Partner with operations and security teams to implement and maintain data security controls, access policies, encryption standards, and compliance requirements to safeguard sensitive and regulated data.
9. Monitor, troubleshoot, and enhance pipeline performance
Continuously monitor data workflows, resolve data processing issues, identify bottlenecks, and enhance performance across ETL / ELT processes, pipelines, and data integrations.
10. Gather requirements and document data workflows
Collaborate with business stakeholders to collect requirements for data pipelines, integrations, and reporting needs. Document data processes, transformation logic, workflow designs, and operational procedures for cross-team visibility and long-term maintainability.
11. Operate effectively both independently and within cross-functional teams
Demonstrate the ability to manage priorities, drive initiatives, and deliver high-quality solutions independently while also contributing collaboratively within cross-functional teams. Engage proactively with engineering, BI, security, operations, and business stakeholders to align on requirements, resolve issues, and deliver integrated data solutions. Communicate clearly, share knowledge, and support team objectives to ensure successful project outcomes and continuous improvement.
The Utah DCC offers a career ladder for Data Engineers and provides growth and professional development opportunities.
To learn more about the Utah DCC visit http://uofuhealth.org/UtahDCC
Learn more about the great benefits of working for University of Utah: benefits.utah.edu
Responsibilities
Data Engineer, III
Design, build, implement, and maintain data processing pipelines for the extraction, transformation, and loading ( ETL ) of data from a variety of data sources. Develop robust and scalable solutions that transform data into a useful format for analysis, enhance data flow, and enable end users to consume and analyze data faster and easier. Write complex SQL queries to support analytics needs. Evaluate and recommend tools and technologies for data infrastructure and processing. Collaborate with engineers, data scientists, data analysts, product teams, and other stakeholders to translate business requirements to technical specifications and coded data pipelines. Work with tools, languages, data processing frameworks, and databases such as R, Python, SQL , MongoDB, Redis, Hadoop, Spark, Hive, Scala, BigTable, Cassandra, Presto, Strom. Work with structured and unstructured data from a variety of data stores, such as data lakes, relational database management systems, and/or data warehouses. Considered highly skilled and proficient in discipline. Conducts complex, important work under minimal supervision and with wide latitude for independent judgment.
Requires a bachelor&rsquo;s (or equivalency) + 6 years or a master&rsquo;s (or equivalency) + 4 years of directly related work experience.
This is a Career-Level position in the General Professional track.
Job Code: P34033
Grade: P21
Expected Pay Range: $64,122 to $124,278
Minimum Qualifications
EQUIVALENCY STATEMENT : 1 year of higher education can be substituted for 1 year of directly related work experience (Example: bachelor&rsquo;s degree = 4 years of directly related work experience).
Department may hire employee at one of the following job levels:
.
Data Engineer, III : Requires a bachelor&rsquo;s (or equivalency) + 6 years or a master&rsquo;s (or equivalency) + 4 years of directly related work experience.
Preferences
&middot; Experience with cloud data services ( AWS preferred: Glue, S3, EC2; bonus for Lambda, Athena, EMR )
Familiarity with building and maintaining data pipelines and integrations in cloud environments.
&middot; Strong experience with Microsoft SQL Server and T- SQL
Proficiency in writing, optimizing, and troubleshooting complex queries, stored procedures, and database objects.
&middot; Development experience in Python for data engineering
Hands-on experience using Python libraries such as Pandas, PySpark, or Boto3 for data processing, automation, or integrations.
&middot; Experience with version control and CI/CD tools (Git, GitHub/GitLab, Jenkins, etc.) Ability to build and maintain automated deployment workflows for data pipelines.
&middot; Ability to read or understand Java is a plus
Helpful for working with legacy connectors, middleware, or JVM -based big data tools.
&middot; Experience with data visualization/reporting tools (Power BI, Tableau, SSRS )
Ability to support analytics teams by preparing data structures suitable for reporting and dashboarding.
&middot; Understanding of data warehouse principles (Star/Snowflake schemas)
Knowledge of how to structure data for analytics and reporting, even if the primary focus is pipeline engineering.
&middot; Working knowledge of database management, data integration patterns, and ETL / ELT frameworks
Comfortable working with relational, cloud, and distributed data platforms.
&middot; Strong analytical and problem-solving skills
Ability to diagnose data issues, performance bottlenecks, and pipeline failures.
&middot; Strong communication skills
Capable of explaining data concepts and pipeline logic to developers, analysts, and non-technical stakeholders.
&middot; Experience working in Agile environments
Proven ability to meet deadlines, prioritize tasks, and deliver high-quality solutions in iterative development cycles.
Applicants will be screened according to preferences.
Type Benefited Staff
Special Instructions Summary
Additional Information
The University is a participating employer with Utah Retirement Systems (&ldquo;URS&rdquo;). Eligible new hires with prior URS service, may elect to enroll in URS if they make the election before they become eligible for retirement (usually the first day of work). Contact Human Resources at (801) 581-7447 for information. Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS&rsquo; post-retirement rules and restrictions. Please contact Utah Retirement Systems at (801) 366-7770 or (800) 695-4877 or University Human Resource Management at (801) 581-7447 if you have questions regarding the post-retirement rules.
This position may require the successful completion of a criminal background check and/or drug screen.
The University of Utah values candidates who have experience working in settings with students and possess a strong commitment to improving access to higher education.
Veterans&rsquo; preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.
Consistent with state and federal law, the University of Utah does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran&rsquo;s status. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.
To request a reasonable accommodation for a disability or if you or someone you know has experienced discrimination or sexual misconduct including sexual harassment, you may contact the Director/Title IX Coordinator in the Office of Equal Opportunity and Title IX ( OEO ). More information, including the Director/Title IX Coordinator&rsquo;s office address, electronic mail address, and telephone number can be located at: https://www.utah.edu/nondiscrimination/ Online reports may be submitted at oeo.utah.edu https://safety.utah.edu/safetyreport This report includes statistics about criminal offenses, hate crimes, arrests and referrals for disciplinary action, and Violence Against Women Act offenses. They also provide information about safety and security-related services offered by the University of Utah. A paper copy can be obtained by request at the Department of Public Safety located at 1658 East 500 South.</div>

Esimplicity

<div>Description:

About Us:
eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow.
Responsibilities:<ul><li>
Responsible for developing, expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams.</li><li>
Support software developers, database architects, data analysts and data scientists on data initiatives and ensure optimal data delivery architecture is consistent throughout ongoing projects.</li><li>
Creates new pipeline and maintains existing pipeline, updates Extract, Transform, Load (ETL) process, creates new ETL feature , builds PoCs with Redshift Spectrum, Databricks, AWS EMR, SageMaker, etc.;</li><li>
Implements, with support of project data specialists, large dataset engineering: data augmentation, data quality analysis, data analytics (anomalies and trends), data profiling, data algorithms, and (measure/develop) data maturity models and develop data strategy recommendations.</li><li>
Operate large-scale data processing pipelines and resolve business and technical issues pertaining to the processing and data quality.</li><li>
Assemble large, complex sets of data that meet non-functional and functional business requirements</li><li>
Identify, design, and implement internal process improvements including re-designing data infrastructure for greater scalability, optimizing data delivery, and automating manual processes</li><li>
Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies</li><li>
Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition?</li><li>
Working with stakeholders including data, design, product and government stakeholders and assisting them with data-related technical issues</li><li>
Write unit and integration tests for all data processing code.</li><li>
Work with DevOps engineers on CI, CD, and IaC.</li><li>
Read specs and translate them into code and design documents.</li><li>
Perform code reviews and develop processes for improving code quality.</li><li>
Perform other duties as assigned.</li></ul>
Requirements:

Required Qualifications:<ul><li>
All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation.</li><li>
Minimum of 8 years of experience as a Data Engineer or in hands-on software development, including at least 4 years using Python, Java, and cloud technologies for building and maintaining data pipelines.</li><li>
Bachelor&rsquo;s degree in Computer Science, Information Systems, Engineering, Business, or a related scientific or technical discipline required.</li><li>
OR In lieu of a degree, candidates may qualify with 10 years of general information technology experience, including at least 8 years of specialized experience.</li><li>
Expert data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.</li><li>
Self-sufficient and comfortable supporting the data needs of multiple teams, systems, and products.</li><li>
Experienced in designing data architecture for shared services, scalability, and performance</li><li>
Experienced in designing data services including API, meta data, and data catalogue.</li><li>
Experienced in data governance process to ingest (batch, stream), curate, and share data with upstream and downstream data users.</li><li>
Ability to build and optimize data sets, &lsquo;big data&rsquo; data pipelines and architectures?</li><li>
Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions?</li><li>
Excellent analytic skills associated with working on unstructured datasets?</li><li>
Ability to build processes that support data transformation, workload management, data structures, dependency and metadata</li><li>
Demonstrated understanding and experience using software and tools including big data tools like Spark and Hadoop; relational databases including MySQL and Postgres; workflow management and pipeline tools such as Apache Airflow, and AWS Step Function; AWS cloud services including Redshift, RDS, EMR and EC2; stream-processing systems like Spark-Streaming and Storm; and object function/object-oriented scripting languages including Scala, Java and Python.?</li><li>
Flexible and willing to accept a change in priorities as necessary.</li><li>
Ability to work in a fast-paced, team-oriented environment</li><li>
Experience with Agile methodology, using test-driven development.</li><li>
Experience with GitHub and Atlassian Jira/Confluence.</li><li>
Excellent command of written and spoken English.</li></ul>
Desired Qualifications:<ul><li>
Federal Government contracting work experience.</li><li>
Databricks Certification, Google&rsquo;s Certified Professional-Data-Engineer certification, IBM Certified Data Engineer &ndash; Big Data certification, CCP Data Engineer for Cloudera</li><li>
Centers for Medicare and Medicaid Services (CMS) or Health Care Industry experience</li><li>
Experience with healthcare quality data including Medicaid and CHIP provider data, beneficiary data, claims data, and quality measure data.</li></ul>
Working Environment: 
eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by your manager. 
Occasional travel for training and project meetings. It is estimated to be less than 5% per year.
Benefits: 
We offer highly competitive salaries and full healthcare benefits.
Equal Employment Opportunity: 
eSimplicity is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, age, status as a protected veteran, sexual orientation, gender identity, or status as a qualified individual with a disability.</div>

GM Financial

<div>Why GMF Technology?
Innovation isn&rsquo;t just a talking point at GM Financial, it&rsquo;s how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We&rsquo;re committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.
Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.
About this role: 
 
The Data Engineer III designs, constructs, tests, and maintains highly scalable data management systems. Data Engineer III is responsible for developing complex data pipelines and ensuring data quality, which involves transforming raw data into a form that can be easily analyzed.</div>
 <div>What makes you an ideal candidate:
<ul><li>Design and build scalable data pipelines and workflows on Azure Databricks, leveraging Delta Lake, Unity Catalog, and Medallion (Bronze/Silver/Gold) Lakehouse architecture.
</li><li>Lead end-to-end migration of legacy SAS analytical workloads to Databricks/PySpark, including SAS macro translation, data validation, and output reconciliation.
</li><li>Drive migration of Oracle databases and stored procedures to Azure-native services (Azure SQL, Synapse Analytics, or Delta Lake), ensuring data fidelity and business continuity.
</li><li>Architect and implement ELT/ETL frameworks supporting batch and near-real-time data ingestion from diverse financial source systems.
</li><li>Design dimensional models, data vault patterns, and lakehouse table structures optimized for financial analytical and regulatory reporting workloads.
</li><li>Build and maintain data pipelines that power AI/ML models, including feature engineering, training data preparation, and inference feeds using Databricks MLflow and Feature Store.
</li><li>Implement LLM and RAG (Retrieval-Augmented Generation) pipeline patterns for internal analytics and tooling where applicable.
</li><li>Design and consume REST APIs for data ingestion, orchestration, and data product exposure; build integrations with third-party financial data providers.
</li><li>Implement event-driven and streaming data patterns using Azure Event Hubs, Service Bus, and Kafka.
</li><li>Enforce data governance policies in Unity Catalog: column-level security, row-level filtering, PII masking, and audit logging.
</li><li>Implement data quality frameworks with automated alerting and lineage tracking.
</li><li>Ensure all data solutions comply with applicable financial regulations: SOX, BCBS 239, GDPR/CCPA, CCAR, DFAST, Basel III/IV.
</li><li>Apply data security controls including encryption, Azure Key Vault management, Private Endpoints, VNet integration, and Managed Identity.
</li><li>Define engineering standards and best practices; lead code reviews and technical design sessions.
</li><li>Mentor junior and mid-level engineers through pairing, reviews, and knowledge sharing.
</li><li>Produce technical documentation including design docs, runbooks, and Architecture Decision Records (ADRs).</li></ul></div>
 <div>Experience
<ul><li>Bachelor's degree required in Computer Science, Information Systems, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field or equivalent experience required.
</li><li>Master's degree strongly preferred in Computer Science, Data Engineering, Data Science, Applied Mathematics, or a related discipline.
</li><li>4-6 years of experience in data engineering or a related field required
</li><li>Experience with Big Data technologies required
</li><li>4-6 years of professional experience in data engineering, data platform development, or a closely related data role.
</li><li>3+ years of hands-on experience with Azure Databricks (PySpark, Delta Lake, Workflows, Unity Catalog).
</li><li>3+ years of cloud data engineering experience on Microsoft Azure (ADF, ADLS Gen2, Synapse, Azure SQL, Event Hubs, Key Vault).
</li><li>2+ years of proven experience in SAS-to-cloud migration &mdash; translating SAS PROC SQL, macros, and data steps to PySpark or SQL equivalents.
</li><li>2+ years of experience leading Oracle database migration to Azure cloud targets.
</li><li>2+ years of experience working in a regulated financial services environment (banking, capital markets, insurance, asset management, or fintech).
</li><li>Demonstrated experience designing and consuming REST APIs and building event-driven integration patterns.
</li><li>Hands-on experience with AI/ML data pipeline development, including feature stores, training data pipelines, and MLflow-based workflows.
</li><li>Proven track record delivering production-grade data systems in complex enterprise environments. 
What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays. 
Our Culture: Our team members define and shape our culture &mdash; an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work &mdash; we thrive. 
Compensation: Competitive pay and bonus eligibility 
Work Life Balance: Flexible hybrid work environment, minimum of 2-days a week in our Irving, TX office.
</li></ul>#LI-Hybrid
#LI-MH1
#GMFJobs</div>

Data Engineer III - Data & AI Enablement

Taco Bell

<div>
 
 Job Description
 
 
 
 
 Who is Taco Bell?
 
 
 
 Taco Bell was born and raised in California and has been around since 1962. We went from selling everyone&rsquo;s favorite Crunchy Tacos on the West Coast to a global brand with 8,500+ restaurants, 350 franchise organizations, that serve 42+ million fans each week around the globe. We&rsquo;re not only the largest Mexican-inspired quick service brand (QSR) in the world, we&rsquo;re also part of the biggest restaurant group in the world: Yum! Brands .
 
 
 Much of our fan love and authentic connection with our communities are rooted in being rebels with a cause. From ensuring we use high quality, sustainable ingredients to elevating restaurant technology in ways that hasn&rsquo;t been done before&hellip; we will continue to be inclusive, bold, challenge the status quo and push industry boundaries.
 
 
 We&rsquo;re a company that celebrates and advocates for different, has bold self-expression, strives for a better future, and brings the fun while we&rsquo;re at it. We fuel our culture with real people who bring unique experiences. We inspire and enable our teams and the world to Live M&aacute;s.
 
 
 At Taco Bell, we&rsquo;re Cultural Rebels. Want to join in on the passion-fueled fun? Learn more about the career below.
 
 
 
 About The Job
 
 
 
 Taco Bell is seeking to add a savvy Data Engineer to join our growing Data and Analytics team. We are looking for a self-driven Data Engineer proficient with SQL &amp; ETL pipelines who is familiar with Cloud technology preferably AWS and has scripting experience. You will work with cross functional partners and third-party vendors to enrich our customer data assets by acquiring, organizing, and aggregating customer data from various sources to construct a full and accurate 360 view of our customer for use in direct/email marketing, targeted media campaigns and analytics. You will build data pipelines to source, analyze and validate data from internal and external customer data sources. This is a great opportunity to work on state-of-the-art data products in a friendly and fun environment.
 
 
 
 Day To Day
 
 
 
 <ul>
 <li>
 Design and develop highly scalable and extensible data pipelines from internal and external sources using cloud technology such as AWS, Airflow, Redshift, Snowflake, EMR, DBT.
 </li>
 <li>
 Implement new source of truth datasets, in partnership with analytics and business teams.
 </li>
 <li>
 Collaborate with data product managers, data scientists, data analysts, and data engineers to document requirements and data specifications.
 </li>
 <li>
 Develop, deploy, and maintain serverless data pipelines using Event Bridge, Kinesis, AWS Lambda, S3, and Glue.
 </li>
 <li>
 Focus on performance tuning, optimization and scalability to ensure efficiency.
 </li>
 <li>
 Build out a robust big data ingestion framework with automation, self-heal capabilities and ability to handle data drifts.
 </li>
 <li>
 Adopt automated and manual test strategies to ensure data product quality
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 Learn and understand how Taco Bell products work and help build end-to-end solutions.
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 Ensure high operational efficiency and quality of your solutions to meet SLAs.
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 Actively participate in code reviews and summarize complex data into usable, digestible datasets.
 
 
 </li>
 </ul>
 
 Is This You?
 
 
 
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 Bachelor&rsquo;s degree in analytics, statistics, engineering, math, economics, computer science, information technology or related discipline
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 2+ years professional experience in cloud technologies
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 2 - 5 years of experience designing and delivering large scale, 24-7, mission-critical data pipelines and features using modern cloud data architectures
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 2+ years of hands-on experience in Strong coding skills with Python/Pyspark/Spark and SQL
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 3+ years of hands-on experience in ETL pipeline such as Informatica, AWS Glue, DBT etc.
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 3+ years of experience working in Redshift, Snowflake or other relevant databases.
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 Expert knowledge in writing complex SQL and ETL development with experience processing extremely large datasets using batch and real time streaming.
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 Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
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 Experience integrating data using streaming technologies such as Kinesis Firehose, Kafka
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 Experience with AWS Ecosystem, especially Lambda, Redshift, Athena, DynamoDB, Airflow and S3
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 Experience integrating data from multiple data sources and file types such as JSON, Parquet, Iceberg formats.
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 Experience supporting and working with cross-functional teams in a dynamic environment
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 Strong quantitative and communication skill
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 Experience with CI/CD tools like Gitlab, Terraform
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 Good To Have:
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 Proficiency with automated testing using tools like pytest
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 Experience contributing to full lifecycle deployments with a focus on testing and quality.
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 Experience with data quality processes, data quality checks, validations, data quality metrics definition and measurement
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 Experience in data quality tools such as Informatica DQ or similar.
 
 
 </li>
 </ul>
 
 Work-Hard, Play-Hard
 
 
 
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 Hybrid work schedule (onsite expectation Tues, Wed, Thurs) and year-round flex day Friday
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 Onsite childcare through Bright Horizons
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 Onsite dining center and game room (yes, there is a Taco Bell inside the building)
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 Onsite dry cleaning, laundry services, carwash,
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 Onsite gym with fitness classes and personal trainer sessions
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 Up to 4 weeks of vacation per year plus holidays and time off for volunteering
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 Generous parental leave for all new parents and adoption assistance program
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 401(k) with a 6% matching contribution from Yum! Brands with immediate vesting
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 Comprehensive medical &amp; dental including prescription drug benefits and 100% preventive care
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 Discounts, free food, swag and&hellip; honestly, too many good benefits to name
 
 
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 </ul>
 Salary Range: $108,300- $127,500 annually + bonus eligibility. This is the expected salary range for this position. Ultimately, in determining pay, we'll consider the successful candidate&rsquo;s location, experience, and other job-related factors.
 
 
 At Taco Bell, we Live M&aacute;s and invite you to do the same. Take a seat at our table. Bring your voice. Bring you, just as you are, a Cultural Rebel. We want you to be your best self!
 
 
 Taco Bell is proud to be an equal opportunity employer and is committed to equity, inclusion, and belonging for all dimensions of diversity. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other protected characteristic.
 
 
 Taco Bell is committed to working with and providing reasonable accommodation to applicants with disabilities or special needs.
 
 
 US Job Seekers/Employees - To view the "Know Your Rights" poster, click here . You may also access Taco Bell&rsquo;s Pay Transparency Policy Statement.
 
 
 Employment eligibility to work with Taco Bell in the U.S. is required as the company will not pursue visa sponsorship for this position.
 
 
 California Residents: For more information about the categories of personal information we collect from you and how we use, sell, and share that information, please see our Privacy Notice for California Employees here .
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