data science and iot manager

Siemens

<div><p>Siemens Smart Infrastructure Electrification and Automation Business Unit is seeking an experienced <b>IoT Solution Engineer.</b></p><p></p><p><b>
What part will you play;</b></p><ul><li>
You will develop innovative/new concepts for linking operating data of electrical components and systems with cloud-based and on-premise data analysis.</li><li>
In order to be able to implement the new requirements of our customers, you support them and the sales department in defining the exact technical requirements.</li><li>
You work closely with our customers and cloud architects to identify innovative communication architecture requirements, data scope, and performance.
</li><li>Your task is to determine the communication architecture in electrical substations, taking into account connected IEDs, sensors, communication protocols, communication hardware, performance and scope of data.</li><li>
Through your technical documentation, bill of materials and cost calculations, you make a decisive contribution into technical and commercial bids.</li><li>
You will support regions about parametrization of IoT solution and developing new solution with exisitng IoT portfolio.</li><li>
In addition, you will contribute to the tendering and execution process for the creation of enquiry/purchasing specifications for IEDs, communication hardware, and parameterization and commissioning services.
</li><li>You will work closely with PLM,OEX and R&amp;D to integrate sensors into electrical components and systems</li></ul><p></p><p><b><br>
What you need to make real what matters;</b></p><ul><li>
University degree in Electrical Engineering or Automation Technology.</li><li>
Relevant professional experience in the development of energy automation systems or industrial automation systems.
</li><li>Experience gained in an international context, with fluency in English and willingness to travel internationally.</li><li>
Knowledge of Condition Monitoring (Temperature, CB monitoring, Partial Discharge, Humidity)</li><li>
Knowledge of IoT gateway configuration software (Sicam Device Manager etc.)</li><li>
Capable of configuring Gateway and cloud app(WinCC OA,Simaris Control,Electrification X)</li><li>
Work experience with Automation and SCADA systems (Siprotec Device, Sicam HMI)</li><li>
Knowledge of field devices (Siprotec Device, 3rd Party IEDs)</li><li>
Capable of troubleshooting</li><li>
Capable of identifying potential risks in the architecture and able to resolve them.</li><li>
Knowledge of Industrial communication protocols (MQTT, OPC UA, IEC 61850, Modbus, SNMP)</li><li>
Knowledge of drawing softwares (Visio, CAD)</li><li>
Capable of Scalability and performances optimizations</li><li>
Capable of designing cyber secure architecture</li><li>
Project management with different teams and coordination with System/Solution engineering</li><li>
Familiar with cloud computing technologies.</li><li>
Knowledge of Electrical Drawing Software
</li><li>Capable for selecting right hardware as per project requirements</li><li>
Able to troubleshoot hardware issues</li><li>
General knowledge for LV,MV Panels (AIS/GIS)</li><li>
Capable of selecting right components for IoT</li><li>
Understanding protection schemas
</li><li>Knowledge of testing and commissioning of IoT field devices.</li><li>
Knowledge for communication protocols</li><li>
Knowledge of EHS rules</li><li>
Knowledge of Internal switchgear configuration tools (NXTools etc.)</li><li>
Knowledge of Internal processes (DTO etc.)</li></ul><p></p><p><b><br>
What We Offer</b></p><div>
<ul><li>Speaking up Culture</li></ul>
<ul><li>Respectful Workplace</li></ul>
<ul><li>Being part of a global work environment</li></ul>
<ul><li>Attractive remuneration package</li></ul>
<ul><li>Excellent recognition tools providing spot awards</li></ul>
<ul><li>Learning &amp; Development opportunities for both personal and professional growth</li></ul>
<ul><li>Leave days for parents and a variety of flexible working models that allow time off for yourself and your family</li></ul>
<ul><li>Creche allowance for mothers</li></ul>
<ul><li>Share matching programs to become a shareholder of Siemens AG</li></ul>
<ul><li>Remote working and remote living flexibility only for relevant positions</li></ul>
<ul><li>Find more benefits here</li></ul></div><p></p><p><br>
Individual benefits are adapted to meet local legal regulations, the requirements of different job profiles, locations, and individual preferences.</p><p>
At Siemens we are always challenging ourselves to build a better future. We need the most innovative and diverse Digital Minds to develop tomorrow &lsquo;s reality.
</p><p>As Siemens we believe physical barriers are not related to potential. Only the potential matters to us. Therefore, we look forward to receiving applications from candidates with physical barriers and chronic illnesses. We support healthy relationships between candidates with barriers and their colleagues because we believe we can create differences together.</p><p>
Siemens is dedicated to quality, equality, and valuating diversity and we welcome applications that reflect the diversity of the communities within which we work.</p><p>
We are looking forward to receiving your online application. Please ensure you complete all areas of the application form to the best of your ability as we will use the data to review your suitability for the role.</p><p>
Please find more information from our web site:</p><p>
https://new.siemens.com/tr/tr.html</p></div>

IoT Solution Engineer

Coca-Cola HBC

<div><div><div><div><div><div><div><div>Egypt (Cairo) &bull; Greece (Athens) &bull; Bulgaria (Sofia)
</div></div></div></div><div><div><div>Information Technology
</div></div></div><div><div><div>Hybrid
</div></div></div><div><div><div>Leaders
</div></div></div></div></div></div><div><div><div><div><div><div><b>Department:</b> Consumer &amp; Customer Platform &amp; Digital Factory
</div><div><b>Location: </b>Egypt, Greece, Bulgaria.<br>
</div><div></div><br>
<div><b>As a Product Configuration Lead &ndash; Commercial IoT </b>within Digital &amp; Technology Platforms Services (DTPS) you will be responsible for the development and lifecycle of IoT products and solutions tailored to commercial use cases such as connected coffee machines, connected vending systems, connected coolers, etc. In this role, you will support development of IoT platform, ensuring efficient data collection, network communication and data management. The ideal candidate has strong market knowledge, expertise in IoT hardware needs, and technical proficiency in IoT systems, including Data processing/storage designs topics, schema registry, IoT Hub or Kafka producers/consumers, enrichment/aggregation pipelines.<br>
</div><div></div><br>
<div><b>YOUR KEY RESPONSIBILITIES:
</b></div><ul><li>Analyze business requirements for IoT architecture solutions, and create development specifications.
</li><li>Recommend and implement IoT components and cloud services
</li><li>Support end-to-end IoT systems design and development, including:
</li></ul><div>o Device connectivity
</div><div>o Data ingestion pipelines
</div><div>o Cloud storage and analytics
</div><ul><li>Integrate IoT platforms with:
</li></ul><div>o Enterprise systems (ERP, CRM)
</div><div>o Data Lake and dashboards
</div><ul><li>Define data models, APIs, and integration layers
</li><li>Ensure security, scalability, and reliability of IoT systems
</li><li>Support deployment and onboarding of devices
</li><li>Provide technical consulting and client-facing presentations
</li><li>Troubleshoot system performance and connectivity issues
</li><li>Stay current on IoT technologies, platforms, regulations, and commercial applications.<br>
</li></ul><div></div><br>
<div><b>ARE THESE YOUR SECRET INGREDIENTS?
</b></div><ul><li>University Degree in a relevant area
</li><li>5+ years of experience in development of IoT solutions with focus on Data &amp; Integration REST APIs, Message brokers (MQTT, Kafka), SQL / NoSQL databases
</li><li>Deep understanding of commercial IoT use cases (e.g., connected drinks equipment, etc.).
</li><li>Strong technical acumen: comfortable working with IoT devices, gateways, cloud platforms, APIs, and dashboards.
</li><li>Prior experience with:
</li></ul><div>o Azure IoT Hub
</div><div>o Experience with Programming &amp; Scripting (Python JavaScript / Node.js&hellip;)
</div><div>o Data &amp; Integration REST APIs, Message brokers (MQTT, Kafka), SQL / NoSQL databases
</div><div>o Networking &amp; Protocols (MQTT, HTTP, AMQP, Device-to-cloud communication models)
</div><div>o Security Device authentication (certificates, keys), Encryption (TLS/SSL), Identity and access management
</div><ul><li>Familiarity with data privacy, security, and compliance requirements in commercial IoT.
</li><li>Experience working with cross-functional teams: engineering, UX/UI, data, sales, and operations.
</li><li>Experience working in startups or early-stage product development environments.
</li><li>English proficiency<br>
</li></ul><div></div><br>
<div><b>ABOUT YOUR NEW TEAM:
</b></div><div>We are Coca-Cola Hellenic, a growth-focused consumer goods business and strategic bottling partner of the Coca-Cola Company. We bottle, distribute and sell an unrivalled range of products in 29 markets in Europe, Africa and Eurasia. As we do, we create value for all stakeholders, support socio-economic growth and build a more positive environmental impact.
</div><div>We bring together more than 30,000 people from over 70 nationalities, coming from five continents. The diversity of our markets, from mature to emerging economies, provides a wide range of attractive opportunities for growth.
</div><div>We nurture our talents. We give opportunities to people across all functions and levels, as well as different geographies, backgrounds and education. We are willing to take a risk on the people we believe in, even if they don&rsquo;t have the perfect experience. We have faith in what every person can be.
</div><div>And although we have so much to be proud of, we always stay humble. We believe the real magic happens &ndash; for us and for you &ndash; when we OPEN UP.<br>
</div><div></div><br>
<div><b>AT COCA-COLA HBC, DIVERSITY HELPS US THRIVE
</b></div><div>At Coca-Cola HBC, we are an inclusive employer that thrives on diversity. This means our environment provides equal opportunities for all, regardless of race, color, religion, age, disability, sexual orientation, or gender identity. Join us in nurturing a culture where everyone belongs and contributes to our collective success.</div><div>
</div></div></div></div></div></div><div></div><div><div><div><h3 class="jobSectionHeader"><b>Benefits
</b></h3></div></div><div><div><div><div><div>Development opportunities</div>
</div></div><div><div><div>Equal opportunity employer</div>
</div></div><div><div><div>IT Equipment</div>
</div></div><div><div><div>Learning programs</div>
</div></div><div><div><div>Work with iconic brands</div>
</div></div><div><div><div>Supportive team</div>
</div></div><div><div><div>Volunteering Opportunities</div>
</div></div><div><div><div>Wellbeing program</div></div></div></div></div></div></div>

Product Configuration Lead - Commercial IoT

Merz Aesthetics

<div><h1 class="jobSectionHeader"><b>IT/OT Data Engineer</b></h1>
<div></div><div><div><div>Location Racine, WI, USA Category Other Job Id DATAE004612 Job Type Full Time Posted Date 05/06/2026</div></div></div></div><p></p>
<br><div><p><b>About Us</b></p>
<p>Founded in 1908, Merz is a successful, family-owned specialty healthcare company with a rich history. As a leading global aesthetics business, our award-winning portfolio of injectables, devices, and skincare products empowers healthcare professionals to enhance confidence through aesthetic medicine. Our purpose is to fuel confidence by helping people look better, feel better, and live better. We believe you do not have to choose between living life and making a living. Live your best life with Merz Aesthetics.</p><p><br>
</p><p><b>A Brief Overview</b></p>
<p>As the organization's initial data engineering hire, this position will develop and support reliable OT to MES/UNS pipelines, integrate enterprise applications (ERP, QMS, complaints) through REST/SOAP APIs, and help establish repeatable integration practices for the data platform. Furthermore, they will collaborate with the first data scientist to build and maintain the organization's digital backbone.</p><p><br>
</p><p><b>What You Will Do</b></p>
<ul><li>Pipeline Engineering (Batch &amp; Streaming) Design, implement, and operate reliable batch and streaming pipelines from OT and enterprise systems to the UNS and analytics platforms, implement event/streaming ingestion (e.g., MQTT, Kafka/Azure Event Hubs) and high-throughput batch workflows, and ensuring performance, scalability, and maintainability.</li>
<li>Systems Integration Connect laboratory and shop-floor equipment to MES, ELN, LIMS and/or the UNS (e.g., OPC UA servers, Kepware, Ignition, industrial gateways), and integrate enterprise applications via REST/SOAP APIs, file drops/EDI, and CDC/connectors (e.g., ERP, QMS, CRM, complaints), with appropriate data contracts and versioning.</li>
<li>Platform, CI/CD, and Reliability Build Infrastructure-as-Code (IaC) environments and implement CI/CD for data pipelines, including automated unit, integration, and data quality testing, and establish observability (logging, metrics, tracing), define SLAs/SLOs/SLIs, and author runbooks to support on-call operations and continuous improvement.</li>
<li>Security, Compliance, and Validation Enforce least-privilege access, OT/IT network segmentation (including DMZ patterns), and secure secrets management and collaborate on CSV/GAMP 5 deliverables and ensure audit trails and change controls aligned to 21 CFR Part 11.</li>
<li>Collaboration and Standards Partner with data science and cross-functional stakeholders to define and maintain data contracts, schemas, and naming conventions and develop reusable connectors, templates, and documentation to accelerate future integrations and promote consistency.</li>
</ul><p><b>Minimum Requirements</b></p>
<ul><li>Bachelor's Degree Data Engineering or Computer Science</li>
<li>3-5 years of data engineering and/or systems integration, with strong exposure to industrial/OT data or high-throughput production systems</li>
<li>3-5 years of hands-on experience with OPC UA, AMQP and SCADA gateways.</li>
<li>3-5 years working with REST/SOAP APIs, schema evolution, and CDC patterns.</li>
<li>2+ years working in GxP environments with awareness of CSV expectations.</li>
</ul><p><b>Preferred Qualifications</b></p>
<ul><li>Experience integrating MES, ERP, QMS, lab equipment and SCADA.</li>
<li>Experience working with Ignition, Litmus, and Fuuz.</li>
<li>Experience working with prompt engineering large language models.</li>
</ul><p><b>Technical &amp; Functional Skills</b></p>
<ul><li>Build/operate batch &amp; streaming pipelines; performance tuning, backpressure handling, and idempotency.</li>
<li>Tooling familiarity (e.g., Spark/Databricks/Synapse, Event Hubs/Kafka/IoT Hub or equivalent).</li>
<li>Protocol familiarity (i.e. OPC UA, MQTT, AMQP, REST/SOAP, file/EDI).</li>
<li>API design/consumption: pagination, throttling, OAuth/SAML/SAS, bulk loads, file drops with integrity checks.</li>
<li>Translating ambiguous business needs into clear data contracts, SLAs, and acceptance criteria.</li>
<li>Strong Python and SQL; Git-based workflows; CI/CD (e.g., GitHub Actions, Azure DevOps).</li>
<li>Proficiency with streaming and batch paradigms (e.g., Kafka/Event Hubs/IoT Hub, or equivalents).</li>
<li>Good knowledge about organization standards, processes and customers, capability to expand this knowledge</li>
<li>Ability to work with moderate guidance</li>
<li>Ability to resolve problems by applying prescribed guidelines and policies</li>
<li>Ability to explain complex information effectively &amp; and support others in straight forward tasks</li>
<li>Good MS Office package skills &amp; familiarity with the most common AV technology</li>
</ul><p><b>Benefits:</b></p>
<ul><li>Comprehensive Medical, Dental, and Vision plans</li>
<li>20 days of Paid Time Off</li>
<li>15 paid holidays</li>
<li>Paid Sick Leave</li>
<li>Paid Parental Leave</li>
<li>401(k)</li>
<li>Employee bonuses</li>
<li>And more!</li>
 </ul><p>Your benefits and PTO start the date you're hired with no waiting period!</p>
<p><b>Work Authorization &amp; Visa Sponsorship: </b>Merz will not sponsor applicants for U.S. work visa status for this opportunity. No sponsorship is available for any employment‑based visas, including but not limited to H‑1B, L‑1, TN, O‑1, E‑3, H‑1B1, F‑1, J‑1, OPT, CPT, or any other employment‑based visa category.</p>
<p><b>Relocation:</b> this position is not eligible for relocations assistance. Candidates must reside in or relocate to the area at their own expense.</p></div>

IT/OT Data Engineer

MA'ADEN

<div><div><div><div><div><p>Role Purpose:
</p><p>The Data Science &amp; Analytics Manager is responsible for overseeing the end-to-end execution of data science and advanced analytics initiatives that support Maaden&rsquo;s operational and business objectives. The role ensures that data science projects are delivered with high quality, reliability, and measurable impact by managing workflows, coordinating cross-functional stakeholders, and maintaining strong alignment with enterprise data, AI, and governance standards.
</p><p>As an operational leader, the Manager translates business needs into actionable analytical work, supervises the development of models, analytical products, and data pipelines, and ensures their successful deployment and adoption across functions. This role plays a critical part in embedding data-driven decision-making within production, maintenance, supply chain, engineering, and other business units by enabling teams to access trusted insights, robust analytical tools, and fit-for-purpose ML/AI solutions.
</p><p>Through effective project management, quality oversight, and close collaboration with technical experts and business partners, the Data Science &amp; Analytics Manager helps accelerate Maaden&rsquo;s transition to a technology-enabled, AI-informed mining enterprise.<br>
</p><p></p><p><b>1. Manage End‑to‑End Data Science Delivery
</b></p><ul><li><p>Oversee the development, implementation, and maintenance of databases and data collection systems.
</p></li><li><p>Manage the lifecycle of ML/AI initiatives&mdash;supporting problem framing, data exploration, feature engineering, model development, validation, and preparation for MLOps deployment.
</p></li><li><p>Ensure delivery of scalable, production‑ready models in alignment with enterprise data governance and AI standards.
</p></li><li><p>Conduct statistical analysis to interpret data insights and support decision‑making.
</p></li><li><p>Apply data mining techniques to uncover patterns, trends, and relationships in large datasets.
</p></li><li><p>Develop predictive models and machine learning algorithms to forecast future outcomes as required.
</p></li><li><p>Create clear data visualizations, dashboards, and reports to effectively communicate findings to business stakeholders.
</p></li><li><p>Collaborate with cross‑functional teams to understand business needs and translate them into data‑driven solutions.
</p></li><li><p>Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins.
</p></li><li><p>Stay updated on emerging techniques, tools, and technologies in data science and analytics.
</p></li><li><p>Promote experimentation, model versioning, automated retraining, and continuous improvement processes.
</p></li><li><p>Recommend enhancements to existing models and analytics workflows for greater efficiency and impact.<br>
</p></li></ul></div></div><br>
<div><div><p><b>2. Data Operations
</b></p><ul><li><p>Partner with data engineering to design, operate, and maintain reliable data pipelines and analytical models, ensuring data accuracy, timeliness, and trustworthiness.
</p></li><li><p>Monitor data quality, resolve data issues, and enforce data best practices across teams.
</p></li><li><p>Support compliance with data security standards and relevant regulations
</p></li><li><p>Supervise the development and deployment of advanced ML models, predictive analytics, GenAI, and optimization solutions, consistent with responsibilities of analytics leadership roles.
</p></li><li><p>Ensure technical rigor across the end‑to‑end ML lifecycle: scoping data engineering modeling validation MLOps monitoring.
</p></li><li><p>Oversee production reliability, model drift management, and continuous improvement.<br>
</p></li></ul></div></div><br>
<div><div><p><b>3. Team Leadership &amp; Capability Building
</b></p><ul><li><p>Manage and grow a multi‑disciplinary team (Lead Specialists, Senior Specialists, Data Scientists). Roles under this manager are explicitly listed in the org structure.
</p></li><li><p>Build technical excellence through coaching on ML, GenAI, statistics, feature engineering, and experimentation.
</p></li><li><p>Foster a culture of innovation, peer review, and reusable modeling frameworks.<br>
</p></li></ul></div></div><br>
<div><div><p><b>4. AI Governance, Quality &amp; Standards
</b></p><ul><li><p>Steward high standards in model explainability, auditability, lineage, and risk management.
</p></li><li><p>Drive compliance with enterprise data governance, PDPL, and model‑risk principles referenced in internal DS/AI qualification guidance.
</p></li><li><p>Ensure adherence to Responsible AI requirements applicable to DS/AI roles (skills and qualifications guidance).
</p></li><li><p>Enforce data quality standards, lineage, and reproducibility across the team&rsquo;s projects.
</p></li><li><p>Support alignment with enterprise governance frameworks, including PDPL compliance.
</p></li></ul></div></div><br>
</div></div><p><b>Minimum Qualifications, Experience and Competencies
</b></p><p><b>Minimum Qualifications:
</b></p><p>Bachelor&rsquo;s degree in computer science, Engineering, Data Science, Mathematics, Applied Mathematics, or Physics.
</p><p><b>Minimum Experience:
</b></p><ul><li><p>10 &ndash; 12+ years&rsquo; experience in advanced analytics, ML/AI engineering, and industrial data science.
</p></li><li><p>Including at least 4 years leading or mentoring analytics professionals.
</p></li><li><p>Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.
</p></li><li><p>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS).
</p></li><li><p>Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams.
</p></li><li><p>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS).
</p></li><li><p>Proven record of enabling cross-functional business impact through scalable, production-grade data science solutions.
</p></li></ul><p><b>Maaden High-Performance Competencies:
</b></p><p><b>Core Competencies
</b></p><ul><li><p>Value realization from ML/analytics initiatives (impact delivered vs. target).
</p></li><li><p>On‑time delivery of analytics roadmap.
</p></li><li><p>Adoption rate and integration of solutions into business workflows.
</p></li><li><p>Model performance stability (drift incidents, uptime).
</p></li><li><p>Team capability maturity and talent development indicators.<br>
</p></li></ul><p></p><p><b>Skills:
</b></p><ul><li><p>Machine Learning &amp; AI Leadership
</p></li><li><p>Programming Expertise
</p></li><li><p>Generative AI Proficiency
</p></li><li><p>Strong Analytical &amp; Statistical Skills
</p></li><li><p>Business Strategy &amp; Product Thinking
</p></li><li><p>Ethics, Governance &amp; Responsible AI
</p></li><li><p>Leadership &amp; People Management</p></li></ul></div>

Manager, Data Science & Analytics

KPMG

<div><p>Known for being a great place to work and build a career, KPMG provides audit, tax and advisory services for organizations in today's most important industries. Our growth is driven by delivering real results for our clients. It's also enabled by our culture, which encourages individual development, embraces an inclusive environment, rewards innovative excellence and supports our communities. With qualities like those, it's no wonder we're consistently ranked among the best companies to work for by Fortune Magazine, Consulting Magazine, Seramount, Fair360 and others. If you're as passionate about your future as we are, join our team.</p>
<p>KPMG is currently seeking a Data Scientist to join our Audit Technology Alliance organization.</p><p>
Responsibilities:</p><ul><li>
Develop sophisticated generative AI solutions; provide technical guidance to a team of data scientists</li><li>
Guide the end-to-end data science lifecycle for key product features; oversee experimentation, rigorous model evaluation, and prompt engineering and optimization</li><li>
Collaborate closely with product managers, audit subject matter experts, and engineering teams to translate complex business requirements into scalable and reliable technical solutions</li><li>
Champion a culture of quality and innovation within engineering teams; identify opportunities to continually improve solutions</li><li>
Drive quality SDLC processes with AI engineering teams; deliver solutions on time to meet business cycle timelines</li><li>
Champion and enhance AI and RAG evaluation frameworks using tools like LangSmith; ensure solutions meet KPMG's standards for quality</li><li>
Provide technical leadership and mentorship to junior data scientists; guide hands-on work in context engineering, model tuning, and advanced data analysis</li><li>
Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment</li></ul><p>
Qualifications:</p><ul><li>
Minimum five years of recent experience in data science or a related machine learning field with a proven track record of delivering AI solutions into production environments</li><li>
PhD or Master's degree from an accredited college or university in computer science, statistics, mathematics, or a related quantitative discipline is required</li><li>
Hands-on expertise with generative AI including extensive experience with LLMs (for example, Azure OpenAI, Google Cloud), RAG pipelines, and AI frameworks such as LangChain/LangGraph or Semantic Kernel</li><li>
Proficient in Python and its data science ecosystem; experienced in building solutions on data platforms like Databricks or Microsoft Fabric and search technologies like Azure AI Search</li><li>
Solid understanding of the software development lifecycle (SDLC) in an agile environment; experienced with version control tools like Git and CI/CD tools within Azure DevOps</li><li>
Exceptional analytical skills; able to communicate complex technical concepts clearly and effectively to both technical and non-technical stakeholders(200TEC)</li></ul>
<div>KPMG LLP and its subsidiaries (&ldquo;KPMG&rdquo;) complies with all local/state regulations regarding displaying salary ranges. If required, the ranges displayed below or via the URL below are specifically for those potential hires who will work in the location(s) listed. Any offered salary is determined based on relevant factors such as applicant's skills, job responsibilities, prior relevant experience, certain degrees and certifications and market considerations. In addition, KPMG is proud to offer a comprehensive, competitive benefits package, with options designed to help you make the best decisions for yourself, your family, and your lifestyle. Available benefits are based on eligibility. Our Total Rewards package includes a variety of medical and dental plans, vision coverage, disability and life insurance, 401(k) plans, and a robust suite of personal well-being benefits to support your mental health. Depending on job classification, standard work hours, and years of service, KPMG provides Personal Time Off per fiscal year. Additionally, each year KPMG publishes a calendar of holidays to be observed during the year and provides eligible employees two breaks each year where employees will not be required to use Personal Time Off; one is at year end and the other is around the July 4th holiday. Additional details about our benefits can be found towards the bottom of our KPMG US Careers site at Benefits &amp; How We Work.</div><div></div><div><br>
Follow this link to obtain salary ranges by city outside of CA:</div>
https://kpmg.com/us/en/how-we-work/pay-transparency.html/?id=8153_9_26
<div><div>KPMG offers a comprehensive compensation and benefits package. KPMG is an equal opportunity employer. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state or local laws. The attached link contains further information regarding KPMG's compliance with federal, state and local recruitment and hiring laws. No phone calls or agencies please.</div><div></div><div><br>
KPMG recruits on a rolling basis. Candidates are considered as they apply, until the opportunity is filled. Candidates are encouraged to apply expeditiously to any role(s) for which they are qualified that is also of interest to them.</div><div></div><div><br>
Los Angeles County applicants: Material job duties for this position are listed above. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, and safeguard business operations and company reputation. Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</div></div></div>

Data Scientist- Manager

Garan, Incorporated

<div>
 <p>
  <strong>
   Overview
  </strong>
 </p>
 <p>
  We are seeking a Microsoft Fabric Data Engineer with Agentic AI experience to design, build, and maintain scalable data solutions within the Microsoft Fabric ecosystem. This role is responsible for developing robust data pipelines, implementing Medallion architecture (Bronze, Silver, Gold layers), and ensuring high-quality, analytics-ready datasets.
 </p>
 <p>
  The ideal candidate will have hands-on experience with Microsoft Fabric components (Data Factory, OneLake, Lakehouse, Warehouse, and Power BI), strong data engineering fundamentals, and the ability to support advanced analytics and AI initiatives.
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design, develop, and maintain end-to-end data pipelines using Microsoft Fabric (Data Factory, Pipelines, Notebooks)
  </li>
  <li>
   Implement and manage Medallion architecture (Bronze, Silver, Gold layers) to ensure data quality, governance, and usability
  </li>
  <li>
   Ingest, transform, and integrate data from multiple structured and unstructured sources
  </li>
  <li>
   Optimize data workflows for performance, scalability, and cost efficiency
  </li>
  <li>
   Build and maintain Lakehouse and Data Warehouse solutions within Fabric
  </li>
  <li>
   Ensure data reliability through monitoring, logging, and error-handling mechanisms
  </li>
  <li>
   Collaborate with stakeholders to translate business requirements into scalable data solutions
  </li>
  <li>
   Enforce data governance, security, and compliance best practices
  </li>
  <li>
   Document data models, pipelines, and system architecture
  </li>
  <li>
   Contribute to roadmap planning and platform evolution
   <br/>
  </li>
 </ul>
 <p>
  <strong>
   Database &amp; Power BI Oversight
  </strong>
 </p>
 <ul>
  <li>
   Design enterprise-grade data models optimized for Power BI and analytics workloads
  </li>
  <li>
   Oversee creation and management of semantic models and datasets within Fabric
  </li>
  <li>
   Oversee dataset performance, refresh strategies, and capacity management in Power BI
  </li>
  <li>
   Implement data modeling best practices (star schema, normalization where appropriate)
  </li>
  <li>
   Support development of dashboards and reports by providing curated, high-quality datasets
  </li>
  <li>
   Manage access control, row-level security (RLS), and data lineage visibility
  </li>
  <li>
   Manage Power BI capacity, dataset refresh strategies, and scalability considerations
  </li>
  <li>
   Collaborate with BI developers to optimize DAX performance and reporting efficiency
  </li>
  <li>
   Monitor usage and adoption metrics to improve data accessibility and usability
   <br/>
  </li>
 </ul>
 <p>
  <strong>
   AI Readiness &amp; Advanced Analytics
  </strong>
 </p>
 <ul>
  <li>
   Prepare and structure data to support AI/ML use cases within Microsoft Fabric and Azure ecosystem
  </li>
  <li>
   Enable feature engineering by delivering clean, enriched, and well-governed datasets
  </li>
  <li>
   Support integration with AI tools such as Azure Machine Learning, Fabric Data Science, and Copilot experiences
  </li>
  <li>
   Implement data pipelines that support real-time or near real-time analytics where needed.
  </li>
  <li>
   Ensure datasets are scalable and aligned with AI model training requirements.
  </li>
  <li>
   Promote best practices for data versioning, reproducibility, and experimentation.
   <br/>
  </li>
 </ul>
 <p>
  <strong>
   Qualifications
  </strong>
 </p>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field.
  </li>
  <li>
   7+ years of experience in data engineering or related roles.
  </li>
  <li>
   Hands-on experience with Microsoft Fabric or closely related tools (Azure Synapse, Azure Data Factory, Power BI).
  </li>
  <li>
   Strong expertise in Medallion architecture and modern data lake/lakehouse patterns.
  </li>
  <li>
   Proven experience building and maintaining data pipelines (ETL/ELT).
  </li>
  <li>
   Proficiency in SQL, Python, and/or Spark.
  </li>
  <li>
   Experience with Lakehouse architectures and distributed data processing.
  </li>
  <li>
   Strong understanding of data modeling and data warehousing concepts.
   <br/>
  </li>
 </ul>
 <p>
  <strong>
   Desired Skills &amp; Competencies
  </strong>
 </p>
 <ul>
  <li>
   Experience with OneLake, Delta Lake, and Fabric-native workloads.
  </li>
  <li>
   Experience with Data Agents, Copilot Studio and Microsoft Foundry
  </li>
  <li>
   Familiarity with CI/CD pipelines for data solutions.
  </li>
  <li>
   Power BI adoption and user satisfaction across business units.
  </li>
  <li>
   Delivery of AI-ready datasets and agentic AI pilot outcomes
  </li>
  <li>
   Security compliance and incident prevention
   <br/>
  </li>
 </ul>
 <p>
  <strong>
   Key Competencies
  </strong>
 </p>
 <ul>
  <li>
   Strong problem-solving and analytical thinking
  </li>
  <li>
   Attention to detail and data quality focus
  </li>
  <li>
   Ability to work cross-functionally with technical and business teams
  </li>
  <li>
   Excellent communication and documentation skills
  </li>
  <li>
   Continuous learning mindset in evolving data and AI technologies
   <br/>
  </li>
 </ul>
 <p>
  <strong>
   Performance Metrics
  </strong>
 </p>
 <ul>
  <li>
   Data integrity and availability across all departments
  </li>
  <li>
   System uptime and query performance
  </li>
  <li>
   Power BI adoption and user satisfaction across business units
  </li>
  <li>
   Reduction in time-to-action based on data insights
  </li>
  <li>
   Successful onboarding and reliability of third-party integrations
  </li>
  <li>
   Delivery of AI-ready datasets and agentic AI pilot outcomes
  </li>
  <li>
   Security compliance and incident prevention
  </li>
  <li>
   Adoption of best practices as informed by industry trends
   <br/>
  </li>
 </ul>
 <p>
  This role is essential for Garan Apparel's enterprise data transformation, integrating Azure and Microsoft Fabric with best practices in data, security, AI readiness, and team collaboration&mdash;while ensuring that every user, from executive to analyst, can understand, trust, and act on data with confidence.
  <br/>
 </p>
 <p>
  <strong>
   Salary
  </strong>
  : $150,000
  <br/>
 </p>
</div>


Data Engineer and Agentic AI Lead

<div><p><b>Job Purpose
</b></p><p>The Manager, Data Domain and Products is accountable for governing, coordinating, and enabling a portfolio of data domains and their associated data products, rather than owning a single domain directly.
</p><p>The role ensures that domain data owners (Principal Specialists) operate within a consistent enterprise framework for data products, governance, quality, and value realization. It acts as the portfolio‑level authority, aligning domain priorities with enterprise strategy, resolving cross‑domain conflicts, and ensuring that data products are delivered as reusable, governed assets rather than siloed solutions.
</p><p>This role is responsible for how data domains operate together, how data products are prioritized and standardized, and how domain outputs collectively support enterprise reporting, operations, controls, and decision‑making.<br>
 </p><p></p><p><b>Key Accountabilities
</b></p><div><ul><li>Provide leadership and oversight across multiple data domains, each owned by a designated domain owner
</li></ul><ul><li>Ensure domain owners apply consistent principles for data ownership, stewardship, modeling, quality, and governance.
</li></ul><ul><li>Balance demand across domains by prioritizing data products based on enterprise value, regulatory need, and readiness.
</li></ul><ul><li>Ensure domain data products integrate cleanly with enterprise platforms and downstream consumers.
</li></ul><ul><li>Act as the primary business‑facing interface for enterprise data domains, translating strategic needs into coordinated domain roadmaps.
</li></ul><ul><li>Enable domain owners to focus on execution by removing blockers, resolving dependencies, and clarifying priorities.
</li></ul><ul><li>Ensure lifecycle artifacts (ownership, definitions, quality expectations, refresh SLAs) are consistently produced across domains.
</li></ul>Lead and develop domain owners, ensuring clarity of role boundaries between domain ownership and enterprise oversight.<br>
<ul><li>
</li></ul></div><p></p><p><b>Minimum Qualification, Experience and Competencies
</b></p><p><b>Minimum Qualification
</b></p><ul><li><p>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, Software Engineering, Cloud Computing, or related field.
</p></li><li><p>MBA or Master&rsquo;s degree or equivalent professional experience is an advantage.
</p></li></ul><p><b>Minimum Experience
</b></p><ul><li>12+ years of experience across data, analytics, or enterprise information management
</li><li>Proven experience leading <b>multiple data domains or portfolios </b>, not just a single domain
</li><li><p>Demonstrated ability to manage senior specialists and influence cross‑functional stakeholders<br>
</p></li></ul><p></p><p><b>Skills:
</b></p><ul><li><p>Portfolio‑level data domain and product management
</p></li><li><p>Enterprise data governance and operating models
</p></li><li><p>Cross‑domain KPI and semantic alignment
</p></li><li><p>Stakeholder management at senior business and technical levels
</p></li><li><p>Ability to translate strategy into coordinated execution across multiple owners</p></li></ul></div>

Manager, Data & AI Platforms

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