data governance engineer

VOIS

<div>
 <strong>
  Who We Are
  <br/>
  <br/>
 </strong>
 VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology &amp; Transformation.
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 As the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next-generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth. With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability.
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 We work with customers across 28 countries from 10 VOIS locations: Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.
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 #VOIS #BeUnrivalled #CreateTheFuture
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 <strong>
  About This Role
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  <br/>
 </strong>
 We are seeking a Data Catalogue Specialist to enable trusted, discoverable, and reusable network data products by owning and evolving metadata, cataloguing, and governance processes within Vodafone&rsquo;s Next Generation Data Infrastructure (NGDI). This role plays a key part in ensuring end‑to‑end data journeys are visible, compliant, and usable through the enterprise data catalogue, Collibra, supporting data‑driven decision‑making across network and digital teams.
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 <strong>
  What You&rsquo;ll Do
  <br/>
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 </strong>
 <ul>
  <li>
   Own and continuously evolve the NGDI data catalogue metamodel, covering data assets, data products, data contracts, domains, markets, critical data elements, lineage, and ownership
  </li>
  <li>
   Enable end‑to‑end discovery of network data products by ensuring consistent and complete metadata across the data lifecycle
  </li>
  <li>
   Design and support automated metadata ingestion and lifecycle workflows, including onboarding, certification, change management, and decommissioning
  </li>
  <li>
   Embed governance, privacy, security, and artificial intelligence compliance by design through metadata controls, classifications, and approval workflows
  </li>
  <li>
   Act as an operational interface between data governance, data quality, and data engineering teams to embed governance best practices into daily delivery
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  </li>
 </ul>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experienced in working with enterprise data catalogues, ideally Collibra, including metamodel configuration and workflow design
  </li>
  <li>
   Knowledgeable in metadata management, data lineage, and data product concepts within cloud‑based environments
  </li>
  <li>
   Familiar with data governance operating models, including stewardship, domain ownership, and federated delivery
  </li>
  <li>
   Comfortable working with data quality concepts such as profiling, certification, critical data elements, and quality rules
  </li>
  <li>
   A collaborative professional who can work effectively across engineering, governance, and business stakeholders
  </li>
  <li>
   Hold a degree in Engineering, Computer Science, or equivalent practical experience in data management, with 3&ndash;5 years of relevant professional experience
  </li>
  <li>
   Additional certifications such as DAMA‑CDMP or Google Cloud Platform are beneficial but not essential
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  </li>
 </ul>
 <strong>
  Not a perfect fit?
  <br/>
  <br/>
 </strong>
 Concerned you may not meet every requirement? Vodafone is committed to creating an inclusive workplace where everyone can thrive. If you are excited about this role but your experience does not align exactly with every aspect of the job description, you are encouraged to apply. You may be the right candidate for this or another opportunity, and the recruitment team will support you in exploring where your skills fit best.
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 <strong>
  What's In It For You
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 <ul>
  <li>
   Exposure to large‑scale, enterprise data and AI transformation programmes within a global organisation
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   The opportunity to shape and mature a critical data capability that underpins network performance and customer experience
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   Collaboration with diverse, international teams across data engineering, governance, and digital functions
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  <li>
   A role that combines strategic thinking with hands‑on delivery in a fast‑evolving data environment
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  </li>
 </ul>
 <strong>
  What Skills You Will Learn
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 <ul>
  <li>
   Advanced enterprise metadata management and data catalogue design at scale
  </li>
  <li>
   Practical application of data governance, privacy, and AI compliance through tooling and workflows
  </li>
  <li>
   Designing automated metadata and data lifecycle processes in cloud‑based data platforms
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  <li>
   Influencing and embedding data management best practices across federated teams and markets
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  </li>
 </ul>
 <strong>
  VOIS Equal Opportunity Employer Commitment
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 Vodafone recognises and celebrates the value of diversity in building a workforce that reflects the customers and communities it serves. No form of discrimination is tolerated. This includes, but is not limited to, discrimination based on race, colour, age, veteran status, gender, pregnancy, maternity or parental status, ethnicity, disability, religion or belief, political affiliation, trade union membership, nationality, citizenship, indigenous status, medical condition, HIV status, neurodiversity, social origin, cultural background, marital or civil partnership status, or socio-economic background.
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 <strong>
  Join Us
  <br/>
  <br/>
 </strong>
 At Vodafone, we&rsquo;re not just shaping the future of connectivity for our customers &ndash; we&rsquo;re shaping the future for everyone who joins our team. When you work with us, you&rsquo;re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.
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 <strong>
  Alert
  <br/>
  <br/>
 </strong>
 Apply for Vodafone jobs only through the official Vodafone Careers website to avoid job scams and fraud.
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 #JDEnhancedByTARA
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 <strong>
  Follow us on social media and #StayConnected
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 </strong>
 <ul>
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   LinkedIn: https://www.linkedin.com/company/vois/
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   Facebook: https://www.facebook.com/voisglobal
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   Instagram: https://www.instagram.com/voisglobal/
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   You can also chat with our employees to learn more about our projects: https://lnkd.in/dpkrcvR2
  </li>
 </ul>
</div>


Data Governance Engineer - Data Catalog (VOIS)

Devoteam

<div>
 <strong>
  Tech for People Unlocks the Future
  <br/>
  <br/>
 </strong>
 At Devoteam, we believe that technology, combined with strong human values, can actively drive change for the better. Discover how Tech for People is shaping the future, creating a positive impact on individuals and the world around us.
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 With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.
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  Devoteam Culture &amp; Values:
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 True innovation is born from a powerful culture, fused with meaningful values.
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  Culture:
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 <strong>
  Fair and courageous
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 </strong>
 Everyone is treated fairly &ndash; this fuels bravery. At Devoteam, we always make fair decisions. We listen and are willing to be challenged, taking courageous decisions as a result. We help our employees to progress at every step and congratulate those who deserve it.
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 <strong>
  Ambition and results
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  <br/>
 </strong>
 Ambition is nurtured at every step &ndash; this drives results. We are ambitious entrepreneurs with a taste for performance, growth and celebrating success. Commitments are always kept as we seek to achieve profitable growth to create value and employment. We aim to bring as much value as possible to our clients, at every touchpoint.
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 <strong>
  Learning and innovating
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  <br/>
 </strong>
 Curiosity and learning are at our core &ndash; this stimulates innovation. At Devoteam, we are curious. We learn and embrace innovation constantly to meet challenges and build partnerships of excellence.
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 <strong>
  Caring and sharing
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 </strong>
 A caring attitude is infused into our culture &ndash; this encourages sharing. We believe in the power of teams, we promote support and collaboration.
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 At Devoteam, we care about our teams and want to work in a positive, productive environment. We support the development of talent and careers,
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 <strong>
  Values:
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 </strong>
 <ul>
  <li>
   Respect
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   Frankness
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  <li>
   Passion
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  </li>
 </ul>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 A Data Engineer is expected to develop, monitor, and optimize data quality rules and processes to ensure reliable and accurate enterprise data.
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 They identify and resolve data anomalies through profiling, cleansing, and validation workflows.
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 The role ensures that business decisions are driven by complete, consistent, and high-integrity data across systems.
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 <strong>
  Key Responsibilities:
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 </strong>
 <ul>
  <li>
   Design, implement, and maintain data quality frameworks, rules, and processes to ensure the accuracy, completeness, and reliability of enterprise data.
  </li>
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   Collaborate with data governance, MDM, and data integration teams to enforce consistent data quality standards across systems.
  </li>
  <li>
   Conduct data profiling, anomaly detection, and validation to identify quality gaps and root causes.
  </li>
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   Develop automated data quality checks and workflows for continuous monitoring and remediation.
  </li>
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   Define and manage key data quality metrics (DQ KPIs) and build dashboards to visualize performance trends.
  </li>
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   Document data quality rules, issue logs, and remediation actions as part of the data governance framework.
  </li>
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   Work closely with business data stewards and domain owners to define data quality expectations and acceptance thresholds.
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   Support audits, compliance reviews, and data management maturity assessments by providing DQ evidence and reports.
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   Lead the design and deployment of scalable data quality solutions across multiple data domains and systems.
  </li>
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   Define enterprise data quality standards, policies, and rule frameworks aligned with governance strategy.
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   Establish data quality scorecards, thresholds, and escalation workflows for high-impact issues.
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   Conduct root cause analysis and lead remediation programs for chronic data issues.
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   Mentor junior engineers and promote data quality best practices across teams.
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   Participate in compliance with the local data management regulations (e.g. NDMO, NDI).
  </li>
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   Design, build, and maintain scalable, secure, and robust data pipelines for efficient data ingestion and transformation, with a strong focus on building quality checks into the infrastructure itself.
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   Collaborate with cross-functional and leadership teams (Data Scientists, Analysts, and Business Leaders) to translate complex business requirements into technical data quality solutions.
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   Research, evaluate, and recommend new data quality tools, technologies, and practices to enhance the reliability, security, and scalability of the data infrastructure.
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  </li>
 </ul>
 <strong>
  Qualifications
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  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Management, or related discipline.
  </li>
  <li>
   5+ years of experience in Data Quality, Data Governance, or Data Engineering roles.
  </li>
  <li>
   Proven hands-on experience with enterprise DQ tools (e.g., Informatica DQ/IDMC, Ataccama, Talend DQ, SAS DQ).
  </li>
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   Strong expertise in data profiling, rule design, standardization, and exception management.
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   Proficiency in SQL and scripting (Python, Shell, or Scala) for advanced data validation.
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   Deep understanding of data governance frameworks and collaboration with data stewards.
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   Ability to design DQ dashboards, scorecards, and KPIs to monitor performance.
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   Strong communication skills for presenting findings and recommendations to business stakeholders.
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   Experience mentoring junior engineers or managing small DQ workstreams.
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   CDMP Associate Certificate and/or Informatica IDQ Certificate and/or IDMC DQ Certificate
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   Experience defining data quality strategy and embedding DQ into enterprise data platforms (MDM, DWH, Data Lake).
  </li>
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   Understanding of data lineage, root cause analysis, and impact assessment.
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   Knowledge of metadata management and integration with data catalogs.
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   Familiarity with regulatory and compliance requirements (e.g., NDMO, NDI).
  </li>
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   Ability to automate DQ workflows through orchestration or CI/CD pipelines.
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  </li>
 </ul>
 <strong>
  Additional Information
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  <br/>
 </strong>
 <strong>
  Business Unit: Data &amp; Intelligence
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 </strong>
 <strong>
  Level: Mid - Senior Level
 </strong>
</div>


Data Engineer

General Motors (GM)

<div><p><b>Job Description
</b></p><p><b>This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI or Austin, TX three times per week, at minimum [or other frequency dictated by the business if more than 3 days].
</b></p><p></p><p><b>The Role
</b></p><p></p><p>The Enterprise Data Governance team is looking for a Level 8 Software Engineer to design, build, and operate enterprise-grade data governance and data platform capabilities. This role focuses on building robust, secure, and scalable services and UIs that enable data discovery, policy enforcement, lineage, and governance workflows across the enterprise.
</p><p>You will work closely with product owners, data governance SMEs, data platform engineers, and security teams to deliver high-quality software that underpins our data governance strategy.
</p><p></p><p><b>What You&rsquo;ll Do
</b></p><ul><li>Design, develop, and maintain full-stack applications that support data governance capabilities (e.g., data catalogs, policy management, approvals, lineage views).
</li><li>Build and enhance React front-end applications using TypeScript and modern JavaScript patterns.
</li><li>Implement Python and Java backend services and APIs leveraging frameworks such as Django and Spring.
</li><li>Design, implement, and optimize relational data models with PostgreSQL and integrate with Cosmos DB where appropriate.
</li><li>Develop and maintain RESTful APIs used by internal services and UIs, ensuring reliability, security, and performance.
</li><li>Apply strong Object-Oriented Programming (OOP) practices, design patterns, and clean code principles across the stack.
</li><li>Build, test, and deploy services on Azure, leveraging managed services, containers, and PaaS capabilities where appropriate.
</li><li>Use GitHub for version control, code reviews, CI/CD workflows, and collaboration.
</li><li>Collaborate with architects, data engineers, and governance SMEs to translate functional and non-functional requirements into technical designs.
</li><li>Contribute to engineering best practices, coding standards, observability, and operational readiness.
</li><li>Participate in on-call and production support rotations as needed, troubleshooting and resolving issues in a timely manner.
</li><li>Mentor junior engineers and contribute to a culture of continuous improvement, accountability, and learning.
</li></ul><p></p><p><b>Your Skills &amp; Abilities (Required Qualifications)
</b></p><ul><li>8+ years of hands-on experience.
</li><li>Bachelor&rsquo;s degree in Computer Science, Software Engineering, Information Systems, or a related technical field; or equivalent practical experience.
</li><li>Strong proficiency in React for building complex, component-based front-end applications.
</li><li>Strong programming skills in Python and Java for backend/API development.
</li><li>Hands-on experience with PostgreSQL (schema design, query optimization, migrations).
</li><li>Professional experience building and operating solutions on Microsoft Azure.
</li><li>Proficiency with TypeScript and JavaScript in production systems.
</li><li>Hands-on experience with Django (or similar Python web frameworks) for API and service development.
</li><li>Hands-on experience with Spring (Spring Boot or related) for Java-based services.
</li><li>Strong understanding and practical use of Object-Oriented Programming concepts and design patterns.
</li><li>Experience designing and implementing REST APIs, including versioning, authentication/authorization, and documentation.
</li><li>Experience with Cosmos DB or equivalent cloud-native NoSQL/datastore technologies.
</li><li>Proficiency with GitHub for source control, branching strategies, pull requests, and CI/CD pipelines.
</li><li>Familiarity with secure coding practices, API security, secrets management, and identity/authorization patterns in the cloud.
</li><li>Relevant professional experience in software engineering, preferably in data platforms, data governance, or other enterprise platform domains.
</li><li>Experience operating in a large-scale, enterprise environment is a plus.
</li><li>Proven ability to deliver high-quality software in an agile environment.
</li><li>Strong problem-solving skills with the ability to decompose complex requirements into iterative, deliverable increments.
</li><li>Effective communication skills with both technical and non-technical stakeholders.
</li><li>Ability to work collaboratively in a global, cross-functional team and handle multiple priorities in a fast-paced environment.
</li></ul><p></p><p><b>What Can Give You a Competitive Advantage (Preferred Qualifications)
</b></p><ul><li>Background in Big Data ecosystems and data analytics platforms (e.g., data lakes, lakehouses, or large-scale data processing systems).
</li><li>Experience with Databricks platform and Databricks certifications.
</li><li>Hands-on experience with Apache Spark (PySpark or Scala/Java) for data processing and analytics workloads.
</li><li>Experience building or integrating with Agentic AI solutions, including:
<ul><li>Orchestrating tool-using agents or workflow-based AI systems.
</li><li>Integrating LLM-based services into backend applications or UIs.
</li><li>Applying AI to automate governance workflows, data quality checks, or metadata enrichment.
</li></ul></li><li>Experience with data governance tooling (e.g., data catalogs, lineage tools, policy engines) or similar enterprise data management platforms.
</li><li>Familiarity with distributed systems concepts (scalability, resilience, consistency) and event-driven architectures.
</li><li>Experience with observability stacks (logging, metrics, tracing) and performance optimization in production environments.
</li></ul><p></p><p>This job may be eligible for relocation benefits.
</p><p></p><p>Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
</p><p></p><p><b>Compensation:
</b></p><ul><li>The expected base compensation for this role is: $160,200 - $220,500. Actual base compensation within the identified range will vary based on factors relevant to the position.
</li><li>Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
</li><li>Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation &amp; holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
</li></ul><p></p><p>GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. THIS INCLUDES DIRECT COMPANY SPONSORSHIP, ENTRY OF GM AS THE IMMIGRATION EMPLOYER OF RECORD ON A GOVERNMENT FORM, AND ANY WORK AUTHORIZATION REQUIRING A WRITTEN SUBMISSION OR OTHER IMMIGRATION SUPPORT FROM THE COMPANY (e.g., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.)
</p><p></p><p>#LI-CC1
</p>&amp;#xa;&amp;#xa;&amp;#xa;&amp;#xa;
<p><b>About GM
</b></p><p>Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
</p><p></p><p><b>Why Join Us
</b></p><p>We believe we all must make a choice every day &ndash; individually and collectively &ndash; to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
</p><p></p><p><b>Benefits Overview
</b></p><p>From day one, we're looking out for your well-being&ndash;at work and at home&ndash;so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting <b>Total Rewards resources </b>.
</p><p></p><p><b>Non-Discrimination and Equal Employment Opportunities (U.S.)
</b></p><p>General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
</p><p></p><p>All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
</p><p></p><p>We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit <b>How we Hire </b>.
</p><p></p><p><b>Accommodations
</b></p><p>General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, <b>email </b>us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.</p></div><p></p>

Staff Software Engineer – Enterprise Data Governance

Qcells

<div><p><b>Description</b>
</p><h3 class="jobSectionHeader"><b>POSITION DESCRIPTION:</b></h3><br>
We are looking for a Senior Data Security Engineer to join our Grid and Energy Services team to own and implement data security governance across the Azure data platform, embedding encryption, access controls and privacy into all data systems. The ideal candidate can set standards and ensure compliance while guiding architecture and risk management across multiple departments within this team.
<h3 class="jobSectionHeader"><b>LOCATION &amp; WORK ARRANGEMENT</b></h3><br>
<b>
This role is remote; however, the candidate(s) will be expected to relocate at their own expense to our onsite Houston location by </b><b><i>Q1 in 2027*</i></b><br>
<ul><li>Q1 2027 is an approximate timeframe and is subject to change at any time</li></ul><h3 class="jobSectionHeader"><b>
RESPONSIBILITIES</b></h3><ul><li>
Design and implement data protection, encryption, and secure access across Azure services (Event Hubs, IoT, Fabric), strengthening pipelines against exfiltration and misuse</li><li>
Build and manage governance frameworks with Microsoft Purview, including cataloging, classification, lineage, and data lifecycle policies</li><li>
Apply privacy-by-design practices (PII minimization, tokenization, anonymization) and ensure controls scale across multi-tenant environments</li><li>
Partner with Security, Legal, and Compliance to align with SOC 2, ISO 27001, and GDPR, delivering audit-ready logging and traceability</li><li>
Embed security and governance into pipelines, IaC, and APIs using policy-as-code and standardized onboarding requirements</li><li>
Monitor governance health via telemetry integrations (Azure Monitor, Log Analytics, App Insights) to support compliance and incident response</li><li>
Define long-term strategy for data security and governance; lead architecture standards, mentor engineers, and advise leadership on risk and compliance</li></ul><h3 class="jobSectionHeader"><b>
REQUIRED QUALIFICATIONS</b></h3><ul><li>
8+ years in data engineering, security, governance, or cloud platforms, with 3+ years focused on data security/governance</li><li>
Strong hands-on experience with Azure data services and security controls</li><li>
Expertise in encryption, key management, and securing data lakes/warehouses on Azure</li><li>
Proficiency in Python, SQL, or KQL for data and analytics workflows</li><li>
Experience building or operating multi-tenant SaaS data platforms on Azure</li><li>
Background in securing real-time/streaming pipelines (Event Hubs or Fabric)</li><li>
Solid understanding of Azure services, CI/CD, and policy-as-code practices</li><li>
Proficient with Git, GitHub, and GitHub Actions for development workflows</li><li>
Experience working in agile environments using JIRA or Azure DevOps</li><li>
BS/MS in Computer Science, Engineering, or a related field preferred</li></ul><h3 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h3><ul><li>
Hands-on experience with Microsoft Purview in production environments</li><li>
Familiarity with Microsoft Fabric governance models and OneLake security</li><li>
Experience securing event-driven and streaming architectures (Event Hubs, IoT)</li></ul><br>
<br>
Hanwha Q CELLS Technologies, Inc. a subsidiary of Hanwha Q CELLS, one of the world&acute;s largest and most recognized photovoltaic manufacturers for its high-performance, high-quality solar cells and modules. It is headquartered in Seoul, South Korea (Global Executive HQ) Talheim, Germany (Technology &amp; Innovation HQ) and Santa Clara, CA, USA (HW and SW Product Development HQ). Through its growing global business network spanning Europe, North America, Asia, South America, Africa, and the Middle East, the company provides excellent services and long-term partnerships to its customers in the utility, commercial, government, and residential markets. Hanwha Q CELLS is a flagship company of Hanwha Group, a FORTUNE Global 500 firm and a Top 7 business enterprise in South Korea.<div><div><div><br>
<b>
PHYSICAL, MENTAL &amp; ENVIRONMENTAL DEMANDS:</b><br>
To comply with the Rehabilitation Act of 1973 the essential physical, mental and environmental requirements for this job are listed below. These are requirements <i>normally expected</i> to perform <i>regular</i> job duties. Incumbent must be able to successfully perform all of the functions of the job with or without reasonable accommodation.</div></div><div><div><div><div><b><br>
Mobility</b></div></div><br>
<div><div><br>
Standing</div><div><br>
20% of time</div></div><br>
<div><div><br>
Sitting</div><div><br>
70% of time</div></div><br>
<div><div><br>
Walking</div><div><br>
10% of time</div></div><br>
<div><div><br>
<b>
Strength</b></div></div><br>
<div><div><br>
Pulling</div><div><br>
up to 10 Pounds</div></div><br>
<div><div><br>
Pushing</div><div><br>
up to 10 Pounds</div></div><br>
<div><div><br>
Carrying</div><div><br>
up to 10 Pounds</div></div><br>
<div><div><br>
Lifting</div><div><br>
up to 10 Pounds</div></div><br>
<div><div><br>
<b>
Dexterity</b> <b>(F = Frequently, O = Occasionally, N = Never)</b></div></div><br>
<div><div><br>
Typing</div><div><br>
F</div></div><br>
<div><div><br>
Handling</div><div><br>
F</div></div><br>
<div><div><br>
Reaching</div><div><br>
F</div></div></div><div><div><div><b><br>
Agility</b> <b>(F = Frequently, O = Occasionally, N = Never)</b></div></div><br>
<div><div><br>
Turning</div><div><br>
F</div></div><br>
<div><div><br>
Twisting</div><div><br>
F</div></div><br>
<div><div><br>
Bending</div><div><br>
O</div></div><br>
<div><div><br>
Crouching</div><div><br>
O</div></div><br>
<div><div><br>
Balancing</div><div><br>
N</div></div><br>
<div><div><br>
Climbing</div><div><br>
N</div></div><br>
<div><div><br>
Crawling</div><div><br>
N</div></div><br>
<div><div><br>
Kneeling</div><div><br>
N</div></div></div></div></div><div></div><p><br>
The salary range is required by the California Pay Transparency Act and may differ depending on the location of those candidates hired nationwide. Actual compensation is influenced by a wide array of factors including but not limited to, skill set, education, licenses and certifications, essential job duties and requirements, and the necessary experience relative to the job&rsquo;s minimum qualifications.</p>
<ul><li>This target salary range is for CA positions only and should not be interpreted as an offer of compensation.</li></ul>
You may view your privacy rights by reviewing Qcells' Privacy Policy or by contacting our HR team for a copy.</div>

Senior Data Security Engineer

Openkyber

<div><p>DataOps Engineer / Azure Data Engineer (Public Health Data Modernization) Location: Remote Position Type: Contract (15 months with multi-year extension options)</p>
<p>Prior experience health care data modernization projects for state projects is highly desired</p>
<b>Job Summary:</b>
<p>We are seeking a highly skilled DataOps Engineer to lead the operationalization of a large-scale public health data infrastructure modernization initiative. This role is critical in establishing a sustainable, staff-owned DataOps foundation to improve the quality, reliability, and usability of state-wide health data. You will work at the intersection of data engineering, quality assurance, and governance, utilizing a modern cloud stack centered on Azure DevOps, Azure Databricks, and AWS Data Lake architectures.</p>
<p>The ideal candidate is not just a technical expert but also a mentor who can perform hands-on co-development with internal teams to build durable organizational capacity.</p>
<b>Key Responsibilities:</b>
<ul><li>Data Quality &amp; Statistical Process Control (SPC): Develop and implement governed, version-controlled downstream Data Quality (DQ) rules and validation frameworks. Establish SPC monitoring for data volumes, timeliness, and distributions, including AI-assisted anomaly detection.</li>
<li>Infrastructure &amp; Pipeline Support: Translate downstream requirements into actionable specifications for upstream ingestion teams. Maintain operational performance metrics and observability dashboards.</li>
<li>Data Governance &amp; Metadata: Build and maintain data glossaries, catalogs, and end-to-end lineage visualizations within established governance tools. Define data contract requirements for external vendors, including schema expectations and QA thresholds.</li>
<li>Analytics &amp; BI Enablement: Develop governed Power BI semantic models (Cost, Quality, Access) and standardized dashboards with integrated DQ/SPC overlays.</li>
<li>Organizational Enablement: Lead role-based training through active co-building sessions. Document all processes, runbooks, and SOPs as living Wikis within Azure DevOps to ensure long-term sustainability.</li>
</ul><b>Required Technical Stack:</b>
<ul><li>Platform: Azure DevOps (Boards, Repos, Pipelines, Wikis).</li>
<li>Data Engineering: Azure Databricks and AWS Data Lake (Medallion Architecture).</li>
<li>Visualization: Power BI (DAX, RLS, semantic modeling).</li>
<li>Automation: Power Automate and SharePoint integration.</li>
<li>Architecture: Experience with native AWS services and complex data ingestion pipelines.</li>
</ul><b>Preferred Qualifications:</b>
<ul><li>Certifications: Microsoft Certified: Azure Data Engineer Associate, Power BI Data Analyst Associate (PL-300), or Databricks Data Engineer Professional.</li>
<li>Domain Expertise: Prior experience with healthcare data infrastructure (e.g., APCD, Medicaid, or clinical datasets).</li>
<li>Management: DAMA CDMP, Lean Six Sigma, or Prosci Change Practitioner certifications.</li>
<li>Agile: SAFe Practitioner or Scrum Master (CSM/PSM).</li>
</ul><p>DataOps Engineer, Azure Data Engineer, Databricks, Azure DevOps Pipelines, Power BI Developer, Healthcare Data Analytics, AWS Data Lake, Medallion Architecture, Data Governance, Statistical Process Control, Metadata Management, Data Quality Engineering, AI Anomaly Detection, Semantic Modeling, DAX, SQL, Python, Public Health IT, Data Lineage, CDMP.</p>
<p><b>For applications and inquiries, contact:</b> hirings@openkyber.com</p></div>

Azure Network Engineer

Zoolatech

<div><div><div><div><div><div><div><div>OVERVIEW</div>
</div><div><div>RESPONSIBILITIES</div>
</div><div><div>REQUIREMENTS</div>
</div></div></div></div><div><div><div><p>ATRC's Data &amp; AI Office is a product and platform execution team &mdash; not a traditional enterprise data function. We build and operate AI-enabled systems that create measurable operational impact across the organization. Our primary output is working software in production.</p><p><b>
What we are building &mdash; now:</b></p><ul><li><p>
An executive reporting portal serving senior leadership, integrating live data from SAP, Microsoft 365, SuccessFactors, and internal systems across multiple operational views (finance &amp; budget, KPIs, technology portfolio, news, wellbeing, and a personalized executive home)</p></li><li><p>
A sovereign data and AI platform: data warehouse, governed pipelines, metadata catalog, and classification enforcement across all entities</p></li><li><p>
Data mesh architecture with federated ownership &mdash; each entity owns its data products; the platform provides governed access</p></li><li><p>
Data readiness for the organization's agentic AI platform &mdash; clean, structured, governed data so AI agents can operate on trusted sources</p></li><li><p>
Operational AI agents delivering real value on top of the agentic platform (document triage, anomaly detection, automated briefings, classification automation)</p></li><li><p>
AI-enabled situational awareness and crisis management systems</p></li><li><p>
Data governance and classification &mdash; managing an active external vendor engagement, bridging framework deliverables into platform-enforced rules, and building the ongoing</p><p>
governance operations the organization requires</p></li></ul><p><b>
How we work:</b></p><ul><li><p>
Small team, high ownership &mdash; every engineer owns a module end-to-end</p></li><li><p>
Two-week sprints with demonstrated output at every review</p></li><li><p>
Ship and improve &mdash; working systems beat perfect designs</p></li><li><p>
Core team owns all architecture and product decisions; external capacity executes within defined scope</p></li><li><p>
Decisions take hours, not weeks. Daily technical choices are made by the engineer.</p></li><li><p>
Feature scope decisions take 24 hours. Architecture pivots take 48 hours. Nothing sits in limbo.</p></li><li><p>
Oversee 5 other workstreams powered by 3rd party vendors within the ecosystem but whom we are ultimately accountable for</p></li></ul>
</div><div><p>Builds the AI capabilities that operations depend on &mdash; classification automation, production agents, and the data bridge to the agentic platform.</p><p><b>
Mission</b></p><p>
Build, own, and continuously improve the AI capabilities across the office's production systems, working under the direction of the Principal AI Engineer. Your scope: automated data classification (remediating what's currently broken), AI-generated briefings, and operational AI agents that deliver real value in weeks.</p><p>
An external partner is building an agentic platform that ATRC will use. Your role in that relationship: define the data contracts the platform consumes, evaluate the sample agents delivered, and build the production agents on top of the platform that go beyond demonstrations into real operational use. You don't build the platform &mdash; you make sure ATRC's data is ready for it and that what gets built on top of it actually works.</p><p><b>
What This Role Owns</b></p><ul><li><p>
Data classification automation: implementing automated classification to remediate current failures, embedding classification into data pipelines alongside the Governance</p></li><li><p>
Lead Operational AI agents: building production agents on top of the agentic platform &mdash; going beyond the sample agents the external partner delivers into real operational workflows</p></li><li><p>
Agentic platform data contracts: defining what data the platform needs, in what format, with what quality guarantees &mdash; working with the Principal AI Engineer</p></li><li><p>
AI service implementation: FastAPI service around LLM APIs with versioned prompt templates</p></li><li><p>
Classification and briefing prompts: structured prompts returning validated JSON with tags, confidence levels, source attribution</p></li><li><p>
Prompt versioning: templates in configuration, editable without code changes</p></li><li><p>
Observability: every LLM call logged with input hash, model version, output, latency, token count</p></li><li><p>
Fallback logic: graceful degradation when LLM APIs are unavailable</p></li><li><p>
Quality evaluation: running precision/recall evaluations against human reviewer samples, reporting results, iterating prompts</p></li></ul><p><b>
Key Decisions</b></p><ul><li><p>
Prompt implementation &mdash; few-shot examples, output parsing, error handling</p></li><li><p>
Confidence threshold tuning based on evaluation results</p></li><li><p>
Context window packing &mdash; what data fits within token budgets</p></li><li><p>
Fallback behavior when APIs degrade</p></li><li><p>
Agent evaluation &mdash; whether an external partner's sample agent is production-ready or needs rework</p></li><li><p>
Bug triage for AI components &mdash; autonomous fix vs. escalate to Principal AI Engineer</p></li></ul><p><b>
Does Not Do</b></p><ul><li><p>
Define AI architecture or agent design patterns (Principal AI Engineer)</p></li><li><p>
Build the agentic platform itself (external partner)</p></li><li><p>
Build the backend API or data pipelines</p></li><li><p>
Fine-tune or train models</p></li><li><p>
Define governance policies (Governance Lead)</p></li></ul><p><b>
Ideal Candidate</b></p><p>
Has shipped an LLM-based feature that non-technical users depend on daily &mdash; and has been responsible when it breaks. Knows the hardest part of applied AI is the fallback, the observability, and the human review loop &mdash; not the prompt. Can evaluate someone else's agent demo and quickly identify whether it's production-ready or held together with string. Works well under a senior AI lead &mdash; takes architectural direction and executes with high quality and speed. Not attached to a particular model &mdash; the job is reliable output.</p>
</div><div><ul><li><p>LLM APIs (Claude, GPT-4, open-weight models) &mdash; structured output, JSON mode, system prompts</p></li><li><p>
Prompt engineering for classification &mdash; zero-shot and few-shot</p></li><li><p>
Python &mdash; async API calls, retry logic, exponential backoff</p></li><li><p>
LLM evaluation &mdash; precision/recall, human-AI agreement scoring</p></li><li><p>
Structured output &mdash; JSON schema enforcement, Pydantic validation</p></li><li><p>
Open-weight / sovereign model APIs (Falcon, Llama, or equivalent)</p></li><li><p>
Token budgeting and context window management</p></li><li><p>
AI observability &mdash; output quality monitoring, anomaly detection</p></li><li><p>
FastAPI and Docker</p></li></ul>
</div></div></div><div><div><div><div><p>Location:
</p><div>Istanbul, Turkey
</div></div><div><p>Seniority:
</p><div>Senior
</div></div><div><p>Technologies:
</p><div>Python
</div></div></div></div><div><div><p>Benefits:
</p><ul><li><b>Paid Vacation
</b></li><li><b>Hybrid Work (home/office)
</b></li><li><b>Sick Days
</b></li><li><b>Sport/Insurance Compensation
</b></li><li><b>Holidays Day Off
</b></li><li><b>English Classes
</b></li><li><b>Training Compensation
</b></li><li><b>Transportation compensation</b></li></ul></div></div></div></div></div></div>

AI Engineer

All Points Logistics

<div><div><p><b>Data Engineer
 </b></p><div></div><div><div>Huntsville , Alabama
</div><p>Direct Hire
</p><p>Apr 9, 2026
</p></div></div><div><b><i>*US CITIZENSHIP REQUIRED*</i></b><br>
<b><i>*ACTIVE DoD SECRET CLEARANCE REQUIRED*</i></b><br>
<b><i>*THIS IS A SIX MONTH POSITION WITH POTENTIAL TO EXTEND*</i></b><br>
<br>
<b>DESCRIPTION OF POSITION/DUTIES:</b><br>
<br>
All Points is seeking a <b>Data Scientist / Data Engineer &ndash; Supply Chain Analytics</b> to support the <b>Army Materiel Command</b> at <b>Redstone Arsenal in Huntsville, AL</b>. This is a <b>six</b><br>
<b>month, full time position with potential to extend</b> and requires <b>100% on site support</b>. There is no remote work option. <b><i>THIS IS A SIX MONTH POSITION WITH POTENTIAL TO EXTEND.</i></b><br>
<br>
The selected candidate will support <b>Army Supply Chain Command Orchestration and Monitoring operations</b> as a hybrid data scientist and data engineer. This role operates at the intersection of <b>data engineering and applied machine learning</b>, owning both the <b>data pipelines</b> that move supply chain data and the <b>models and analytics</b> that extract operational insight.<br>
Working under the technical direction of a Senior AI Solutions Engineer, the candidate will build, optimize, and maintain production grade analytics that enable <b>supply chain mapping, disruption detection, and risk visibility</b> across priority weapons systems and materiel programs. This is a <b>mission driven, production cadence role</b>, not a research only position.<br>
<br>
<b><i>Duties may include but are not limited to:</i></b>
<ul><li>Build and maintain supply chain mapping constructs that trace multi-tier supplier relationships, component dependencies, foreign ownership indicators, and program linkages</li>
<li>Design, optimize, and maintain data pipelines ingesting supply chain data from government and commercial sources into Snowflake and downstream analytics environments</li>
<li>Develop and enhance disruption alerting models to detect supply chain stress signals, including single-source dependencies, supplier financial distress, geopolitical exposure, and lead-time anomalies</li>
<li>Apply machine learning and AI techniques to supply chain datasets, including entity resolution, anomaly detection, risk scoring, and predictive modeling</li>
<li>Write, optimize, and maintain complex SQL queries and Python-based transformation logic against Snowflake data warehouses</li>
<li>Produce analytic outputs that support Red Team vulnerability assessments, Blue Team mitigation planning, and executive decision-support dashboards</li>
<li>Participate in data quality validation, confidence scoring, and model monitoring workflows</li>
<li>Maintain pipeline documentation, data dictionaries, model artifacts, and data provenance per program governance standards</li>
<li>Support government-directed onboarding of new data sources, including schema mapping and integration into existing pipelines</li>
</ul><b>EDUCATION:
</b><ul><li>Bachelor&rsquo;s degree from an accredited college in a related discipline</li>
</ul><b>YEARS OF EXPERIENCE:
</b><ul><li>Eight (8) to ten (10) years of relevant experience preferred<br>
Minimum of four (4) years of combined data science and data engineering experience required</li>
</ul><b>SKILLS/CERTIFICATIONS:</b>
<ul><li>Demonstrated supply chain domain knowledge, including supplier networks, procurement data, logistics, or defense materiel programs</li>
<li>Proficiency in Python for data engineering, analytics, and machine learning workflows</li>
<li>Strong SQL skills, including complex queries, window functions, and performance optimization</li>
<li>Hands-on Snowflake experience in a production analytics environment</li>
<li>Experience building and maintaining ETL/ELT pipelines using orchestration frameworks (Airflow, dbt, Spark, or equivalent)</li>
<li>Experience applying ML or AI techniques to real-world structured datasets in production or near-production environments</li>
<li>Strong documentation practices supporting data lineage, auditability, and governance</li>
<li>Experience with defense supply chain datasets (CAGE codes, NSNs, DLA/GIDEP) preferred</li>
<li>Experience with entity resolution, graph-based supply chain mapping, or network analysis preferred</li>
<li>Familiarity with AWS or other cloud data platforms in GovCloud or regulated environments preferred</li>
<li>Familiarity with CUI handling and NIST 800-171 data governance requirements preferred</li>
</ul><b>SECURITY CLEARANCE:
</b><ul><li>US Citizenship required</li>
<li><b>Active DoD Secret security clearance required</b></li>
</ul>Positions with All Points are Full-Time, Direct, and include a comprehensive benefits package. For more information, please visit our Career Portal:<br>
<b>https://www.allpointsllc.com/careers/</b><br>
<br>
<b>ALL POINTS IS AN EQUAL OPPORTUNITY EMPLOYER</b></div></div>

2033 Cleared Data Scientist/Data Engineer – Supply Chain Analytics (Secret Clearance Required)

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