lead data architect

Tandem Search

<div>
 
 A premier global consulting firm is seeking a Lead Data Architect to design and lead the implementation of sophisticated, scalable data architectures that drive transformative business insights for their clients.
 
 
 
 
 
 This role is ideal for a seasoned expert passionate about building robust database solutions, optimizing data systems, and leading complex data migrations.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Architect and implement effective database solutions and models to store and retrieve company data.
 </li>
 <li>
 Analyze client operations, applications, and programming to identify database structural requirements.
 </li>
 <li>
 Ensure all database implementations comply with internal and external regulations.
 </li>
 <li>
 Oversee the installation of information systems and lead data migrations from legacy systems to new solutions.
 </li>
 <li>
 Monitor system performance through regular tests, troubleshoot issues, and integrate new features.
 </li>
 <li>
 Develop accurate database design and architecture reports for management and executive teams.
 </li>
 <li>
 Recommend and implement solutions to improve new and existing database systems.
 </li>
 <li>
 Educate and mentor team members through training and individual support, providing timely resolution to system problems.
 </li>
 </ul>
 
 
 
 
 
 Ideal Candidate Profile
 
 
 
 
 
 <ul>
 <li>
 Proven work experience as a Data Architect, Data Scientist, Data Analyst, or similar role.
 </li>
 <li>
 In-depth understanding of database structure principles and proven expertise in SQL and Oracle.
 </li>
 <li>
 Experience applying data mining, segmentation, and statistical techniques to solve complex problems.
 </li>
 <li>
 Familiarity with data visualization tools (e.g., Tableau, D3.js, and R).
 </li>
 <li>
 Excellent organizational and analytical abilities, with outstanding problem-solving skills.
 </li>
 <li>
 Strong written and verbal communication skills.
 </li>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Computer Engineering, or a relevant field.
 </li>
 <li>
 A minimum of 8+ years of relevant work experience; prior consulting experience is a strong plus.
 </li>
 </ul>
 
 
 
 
 We are specifically interested in professionals with experience at top-tier firms such as McKinsey &amp; Company, BCG, Bain &amp; Company, Kearney, Strategy&amp;, Oliver Wyman, Roland Berger, or Arthur D. Little.
 
 
 
 
 
 
 Apply Now
 
 
 
 
 
 
 If you are a collaborative leader ready to architect the future of data and drive innovation across industries, we encourage you to apply.
 
</div>

Lead Data Architect

QBurst

<div><h2 class="jobSectionHeader">Description:</h2>
We are seeking an experienced Architect to drive our data and AI streams. The ideal candidates are not just technical experts but also strategic thinkers who can act as independent consultants, guiding projects from concept to production. They should have a proven track record of designing, developing, and deploying robust, scalable, and real-world AI systems.<h3 class="jobSectionHeader">
Responsibilities:</h3><ul><li>
Architect and Design: Lead the architecture, design, and implementation of highly scalable and reliable data platforms and AI systems. This includes building foundational data pipelines, data lakes, and real-time data streams</li><li>
AI/ML Development: Drive the end-to-end lifecycle of machine learning models, from experimentation and feature engineering to deployment, monitoring, and maintenance in a production environment (MLOps)</li><li>
Technical Leadership: Act as a technical lead, mentoring junior engineers, setting best practices, and performing code reviews to ensure high-quality and efficient code</li><li>
Strategic Consultation: Work directly with our client&rsquo;s technical and product teams to understand requirements and translate them into a clear technical vision and roadmap</li><li>
Innovation: Stay current with the latest advancements in AI, LLMs, machine learning, and data engineering to introduce new technologies and methodologies that improve our capabilities</li><li>
Collaboration: Partner with cross-functional teams, including product managers, data scientists, and software engineers, to deliver integrated solutions</li></ul>
Requirements<ul><li>
Extensive Experience: 8+ years of hands-on experience in AI/ML and data engineering</li><li>
Scalable AI Systems: Proven experience designing and implementing scalable AI systems in a production environment. This includes a deep understanding of MLOps principles and tools</li><li>
Technical Expertise:<ul><li>
Data Technologies: Proficiency with modern data platforms and tools (e.g., Databricks, Snowflake, Apache Spark, Flink, Airflow, Kafka)</li><li>
AI/ML Frameworks: Strong command of at least one major ML framework (e.g., TensorFlow, PyTorch). Experience with large language models (LLMs) and other generative AI technologies is a significant plus</li><li>
Gen AI Frameworks: Exposure to LLMs like Open AI, Claude, Gemini etc and frameworks like LangChain, LangGraph, LangSmith, LangFlow etc</li><li>
Programming Languages: Expert-level proficiency in at least one key programming language (e.g., Python, Scala, Java)</li></ul></li><li>
Cloud Platforms: Extensive experience with one or more major cloud providers (AWS, GCP, or Azure), including their data and AI services</li><li>
Data Engineering : Exposure to big data processing using PySpark or Databricks is an added advantage while not a mandatory skill</li><li>
Problem-Solving: Exceptional analytical and problem-solving skills, with the ability to tackle complex, ambiguous challenges independently</li><li>
Communication: Excellent communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders</li></ul><h4 class="jobSectionHeader">
Preferred Qualifications:</h4><ul><li>
Experience with a diverse set of AI applications, such as computer vision, natural language processing, or time-series analysis</li><li>
Background in an industry with complex data requirements (e.g., finance, e-commerce, healthcare)</li><li>
A portfolio of open-source contributions demonstrating real-world projects and technical depth</li></ul></div>

Lead Engineer/Associate Architect - Data/AI

<div></div><div><div><div><div><ul><div>7 - 9 Years</div>
<div></div><div>1 Opening</div>
 <div>Bangalore, Hyderabad, Pune, Trivandrum</div></ul></div><div> 
<div><div>
</div></div></div></div><div></div><div><h3 class="jobSectionHeader">Role description</h3>
<div>Role Proficiency:

This role requires proficiency in developing data pipelines including coding and testing for ingesting wrangling transforming and joining data from various sources. The ideal candidate should be adept in ETL tools like Informatica Glue Databricks and DataProc with strong coding skills in Python PySpark and SQL. This position demands independence and proficiency across various data domains. Expertise in data warehousing solutions such as Snowflake BigQuery Lakehouse and Delta Lake is essential including the ability to calculate processing costs and address performance issues. A solid understanding of DevOps and infrastructure needs is also required.

Outcomes:
<div>
<ul><li>Act creatively to develop pipelines/applications by selecting appropriate technical options optimizing application development maintenance and performance through design patterns and reusing proven solutions. Support the Project Manager in day-to-day project execution and account for the developmental activities of others.</li></ul>
<ul><li>Interpret requirements create optimal architecture and design solutions in accordance with specifications.</li></ul>
<ul><li>Document and communicate milestones/stages for end-to-end delivery.</li></ul>
<ul><li>Code using best standards debug and test solutions to ensure best-in-class quality.</li></ul>
<ul><li>Tune performance of code and align it with the appropriate infrastructure understanding cost implications of licenses and infrastructure.</li></ul>
<ul><li>Create data schemas and models effectively.</li></ul>
<ul><li>Develop and manage data storage solutions including relational databases NoSQL databases Delta Lakes and data lakes.</li></ul>
<ul><li>Validate results with user representatives integrating the overall solution.</li></ul>
<ul><li>Influence and enhance customer satisfaction and employee engagement within project teams.</li></ul>
</div>
Measures of Outcomes:
<div>
<ul><li>TeamOne's Adherence to engineering processes and standards</li></ul>
<ul><li>TeamOne's Adherence to schedule / timelines</li></ul>
<ul><li>TeamOne's Adhere to SLAs where applicable</li></ul>
<ul><li>TeamOne's # of defects post delivery</li></ul>
<ul><li>TeamOne's # of non-compliance issues</li></ul>
<ul><li>TeamOne's Reduction of reoccurrence of known defects</li></ul>
<ul><li>TeamOne's Quickly turnaround production bugs</li></ul>
<ul><li>Completion of applicable technical/domain certifications</li></ul>
<ul><li>Completion of all mandatory training requirementst</li></ul>
<ul><li>Efficiency improvements in data pipelines (e.g. reduced resource consumption faster run times).</li></ul>
<ul><li>TeamOne's Average time to detect respond to and resolve pipeline failures or data issues.</li></ul>
<ul><li>TeamOne's Number of data security incidents or compliance breaches.</li></ul>
</div>
Outputs Expected:

Code:
<div>
<ul><li>Develop data processing code with guidance 
ensuring performance and scalability requirements are met.</li></ul>
<ul><li>Define coding standards 
templates 
and checklists.</li></ul>
<ul><li>Review code for team and peers.</li></ul></div> 
 
Documentation:
<div>
<ul><li>Create/review templates 
checklists 
guidelines 
and standards for design/process/development.</li></ul>
<ul><li>Create/review deliverable documents 
including design documents 
architecture documents 
infra costing 
business requirements 
source-target mappings 
test cases 
and results.</li></ul></div> 
 
Configure:
<div>
<ul><li>Define and govern the configuration management plan.</li></ul>
<ul><li>Ensure compliance from the team.</li></ul></div> 
 
Test:
<div>
<ul><li>Review/create unit test cases 
scenarios 
and execution.</li></ul>
<ul><li>Review test plans and strategies created by the testing team.</li></ul>
<ul><li>Provide clarifications to the testing team.</li></ul></div> 
 
Domain Relevance:
<div>
<ul><li>Advise data engineers on the design and development of features and components 
leveraging a deeper understanding of business needs.</li></ul>
<ul><li>Learn more about the customer domain and identify opportunities to add value.</li></ul>
<ul><li>Complete relevant domain certifications.</li></ul></div> 
 
Manage Project:
<div>
<ul><li>Support the Project Manager with project inputs.</li></ul>
<ul><li>Provide inputs on project plans or sprints as needed.</li></ul>
<ul><li>Manage the delivery of modules.</li></ul></div> 
 
Manage Defects:
<div>
<ul><li>Perform defect root cause analysis (RCA) and mitigation.</li></ul>
<ul><li>Identify defect trends and implement proactive measures to improve quality.</li></ul></div> 
 
Estimate:
<div>
<ul><li>Create and provide input for effort and size estimation 
and plan resources for projects.</li></ul></div> 
 
Manage Knowledge:
<div>
<ul><li>Consume and contribute to project-related documents 
SharePoint 
libraries 
and client universities.</li></ul>
<ul><li>Review reusable documents created by the team.</li></ul></div> 
 
Release:
<div>
<ul><li>Execute and monitor the release process.</li></ul></div> 
 
Design:
<div>
<ul><li>Contribute to the creation of design (HLD 
LLD 
SAD)/architecture for applications 
business components 
and data models.</li></ul></div> 
 
Interface with Customer:
<div>
<ul><li>Clarify requirements and provide guidance to the Development Team.</li></ul>
<ul><li>Present design options to customers.</li></ul>
<ul><li>Conduct product demos.</li></ul>
<ul><li>Collaborate closely with customer architects to finalize designs.</li></ul></div> 
 
Manage Team:
<div>
<ul><li>Set FAST goals and provide feedback.</li></ul>
<ul><li>Understand team members' aspirations and provide guidance and opportunities.</li></ul>
<ul><li>Ensure team members are upskilled.</li></ul>
<ul><li>Engage the team in projects.</li></ul>
<ul><li>Proactively identify attrition risks and collaborate with BSE on retention measures.</li></ul></div> 
 
Certifications:
<div>
<ul><li>Obtain relevant domain and technology certifications.</li></ul>
</div>
Skill Examples:
<div>
<ul><li>Proficiency in SQL Python or other programming languages used for data manipulation.</li></ul>
<ul><li>Experience with ETL tools such as Apache Airflow Talend Informatica AWS Glue Dataproc and Azure ADF.</li></ul>
<ul><li>Hands-on experience with cloud platforms like AWS Azure or Google Cloud particularly with data-related services (e.g. AWS Glue BigQuery).</li></ul>
<ul><li>Conduct tests on data pipelines and evaluate results against data quality and performance specifications.</li></ul>
<ul><li>Experience in performance tuning.</li></ul>
<ul><li>Experience in data warehouse design and cost improvements.</li></ul>
<ul><li>Apply and optimize data models for efficient storage retrieval and processing of large datasets.</li></ul>
<ul><li>Communicate and explain design/development aspects to customers.</li></ul>
<ul><li>Estimate time and resource requirements for developing/debugging features/components.</li></ul>
<ul><li>Participate in RFP responses and solutioning.</li></ul>
<ul><li>Mentor team members and guide them in relevant upskilling and certification.</li></ul>
</div>
Knowledge Examples:

Knowledge Examples
<div>
<ul><li>Knowledge of various ETL services used by cloud providers including Apache PySpark AWS Glue GCP DataProc/Dataflow Azure ADF and ADLF.</li></ul>
<ul><li>Proficient in SQL for analytics and windowing functions.</li></ul>
<ul><li>Understanding of data schemas and models.</li></ul>
<ul><li>Familiarity with domain-related data.</li></ul>
<ul><li>Knowledge of data warehouse optimization techniques.</li></ul>
<ul><li>Understanding of data security concepts.</li></ul>
<ul><li>Awareness of patterns frameworks and automation practices.</li></ul>
</div>
Additional Comments:

Responsibilities: &bull; Design, configure, and deploy Amazon Connect contact center solutions. &bull; Integrate Amazon Connect with other AWS services (Lambda, Lex, S3, DynamoDB, etc.). &bull; Develop and maintain custom contact flows, routing profiles, and agent hierarchies. &bull; Implement real-time and historical reporting using AWS tools and SQL queries. &bull; Collaborate with DevOps and engineering teams to ensure seamless deployment and monitoring. &bull; Troubleshoot and optimize existing Amazon Connect implementations. &bull; Ensure compliance with security and data privacy standards. &bull; Provide technical documentation and training to internal stakeholders. Required Skills &amp; Qualifications: Amazon Connect Expertise (Expanded): &bull; Build and optimize complex contact flows using Amazon Connect&rsquo;s drag-and-drop interface. &bull; Implement dynamic routing logic based on customer inputs, agent availability, and business rules. &bull; Configure whisper prompts, queue hold messages, and error handling flows. &bull; Define agent hierarchies, routing profiles, and user permissions. &bull; Set up queues, hours of operation, and escalation paths. &bull; Monitor agent performance and optimize staffing using historical and real-time metrics. &bull; Connect Amazon Connect with AWS Lambda for serverless backend logic. &bull; Use Amazon Lex for conversational IVR and chatbot capabilities. &bull; Store and retrieve customer data using Amazon DynamoDB or S3 during interactions. &bull; Customize and extend reporting using Amazon Connect&rsquo;s Contact Trace Records (CTR). &bull; Use CloudWatch for monitoring, ing, and logging of contact center metrics. &bull; Implement role-based access control using AWS IAM. &bull; Ensure encryption of data in transit and at rest. &bull; Maintain compliance with industry standards (e.g., HIPAA, PCI-DSS) where applicable. &bull; Integrate with CRMs like ServiceNow. &bull; Use APIs and webhooks to connect with external systems for ticketing, customer data, and notifications. &bull; Diagnose call quality issues, latency, and flow errors. AWS Development Skills: &bull; Proficiency in AWS Lambda (Node.js or Python). &bull; Experience with API Gateway, CloudFormation, IAM, S3, DynamoDB, and CloudWatch. &bull; Familiarity with AWS SDKs and CLI tools. &bull; Understanding of serverless architecture and event-driven design. SQL &amp; Data Handling: &bull; Ability to write basic to intermediate SQL queries. &bull; Experience with relational databases (e.g., PostgreSQL). &bull; Understanding of data modeling and reporting. &bull; Experience with Dynamodb General Skills: &bull; Strong problem-solving and analytical skills. &bull; Excellent communication and documentation abilities. &bull; Ability to work independently and in a team environment. &bull; Agile/Scrum experience is a plus. Preferred Qualifications: &bull; AWS Certified Solutions Architect or Developer. &bull; Experience with Amazon Lex, Polly, and Transcribe. &bull; Knowledge of contact center KPIs and analytics.</div>
<h3 class="jobSectionHeader">Skills</h3>
<div>Aws Services,amazon connect,Sql,Analytical</div></div></div></div>
 <div><h3 class="jobSectionHeader">About UST</h3>
<div>UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world&rsquo;s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients&rsquo; organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact&mdash;touching billions of lives in the process.</div></div>

Lead II - Data Engineering

Open Data Science

A software development company is looking for a talented, long-term Lead DS Researcher.We're looking for a Lead Data Science Researcher who thrives in research-heavy environments and enjoys exploring uncharted territory with the support of a strong technical team.This is a unique opportunity to drive forward new ideas and applications, not just optimize existing ones.About the companyCompany Top Remote TalentThe company is a team of experts providing analytical services to healthcare clients. You will join an international team of first class professionals who are passionate to create products that improve quality of medical services.ResponsibilitiesYou will lead a compact team of two data scientists, guiding them on high-impact research initiatives and experimental projects. Your role will involve pushing the boundaries of applied machine learning - especially in the context of medical and clinical data - and turning complex problems into innovative solutions.Requirements What we're looking for: Exceptional analytical and statistical skills-comfortable with uncertainty, inference, and experimentation;Strong background in different areas of ML (traditional classification and regression techniques, recommender systems, text data, clustering, etc.);Solid experience with deep learning frameworks like PyTorch or TensorFlow;Excellent Python skills (beyond Jupyter Notebooks) - ability to build clean, testable, production-ready code;Familiarity with medical or life science data is a strong plus;Expertise in SQL, Pandas, Scikit-learn, and modern data workflows;Comfortable working in Google Cloud Platform (GCP) environments. Bonus points for experience with: State-of-the-art NLP models, Transformers, Agentic Approaches for mixed (temporal and text) data analysis and summarization;Experience with pipeline orchestration tools like Airflow, Argo, etc.;Proven Experience with Anomaly Detection and Forecasting with explainability for temporal and mixed data;Intermediate+ English - ability to participate in written discussions with international teams and clients.Working conditions Benefits: Join a mission-driven team working at the intersection of data, medicine, and impact;Work on meaningful challenges with long-term value for public health and healthcare quality;Collaborate with top-tier experts in a culture that values curiosity, autonomy, and innovation;Fully remote-friendly setup with flexibility and trust at the core. Contacts Log In Only registered users can open employer contacts.<img src="https://www.jobg8.com/Tracking.aspx?oz7KrmCIbPRwpsVo3HMc9YhoUv2EUbwje" width="0" height="0" />

Lead Data Science Researcher

Hays

<div>
 
 
 Location:
 
 Abu Dhabi, United Arab Emirates
 
 
 
 Industry:
 
 Quantitative Research
 
 
 
 
 
 We are looking for a highly motivated and experienced
 
 Lead Data Scientist
 
 to head our data science team in Abu Dhabi.
 
 
 
 
 
 
 About the Role:
 
 
 
 As Lead Data Scientist, you will be responsible for defining and implementing advanced data science solutions, leading a team of 10 professionals. This role requires strong technical expertise, strategic leadership, and hands-on involvement in developing machine learning architectures and models.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Provide technical leadership to a team of data scientists and machine learning engineers.
 </li>
 <li>
 Design and implement data solutions for applications in BFSI, quantitative research, and asset management.
 </li>
 <li>
 Develop and optimize ML models, including LLMs and NLP pipelines, in multi-GPU environments.
 </li>
 <li>
 Define scalable and robust architectures for data processing and predictive modeling.
 </li>
 <li>
 Act as the team&rsquo;s technical reference, promoting best practices and continuous innovation.
 </li>
 <li>
 Communicate technical insights clearly to both technical and non-technical stakeholders.
 </li>
 <li>
 Collaborate with cross-functional teams to integrate data capabilities into products and workflows.
 </li>
 </ul>
 
 
 
 
 
 What We&rsquo;re Looking For:
 
 
 <ul>
 <li>
 7+ years of experience in applied data science within BFSI, quantitative research, or asset management.
 </li>
 <li>
 Proven experience in technical leadership and team management.
 </li>
 <li>
 Strong expertise in Machine Learning, LLMs, NLP, and foundational models.
 </li>
 <li>
 Hands-on experience with Python, TensorFlow, PyTorch, Scikit-learn, among others.
 </li>
 <li>
 Ability to work hands-on in complex technical environments.
 </li>
 <li>
 Excellent communication skills in English (written and verbal).
 </li>
 </ul>
 
 
 
 
 
 Academic Background:
 
 
 <ul>
 <li>
 Master&rsquo;s or PhD in relevant fields, preferably from top-tier universities (Ivy League, Oxbridge, ETH, etc.)
 </li>
 </ul>
 
 
 
 
 
 What We Offer:
 
 
 <ul>
 <li>
 Competitive, tax-free salary.
 </li>
 <li>
 Visa sponsorship (if needed).
 </li>
 <li>
 Health insurance for you and your family.
 </li>
 <li>
 Annual return ticket to your home country.
 </li>
 </ul>
 
 
</div>

Lead Data Scientist

University Federal Credit Union

<div>Job Summary

The Data Governance Lead designs, implements, and maintains a comprehensive data governance framework that ensures data is treated as a strategic asset across the organization. This role collaborates with the Vice President of Insights and Innovation, Data Product Owner, and agile team members to set standards, policies, and processes for data management, quality, and compliance. The Data Governance Lead empowers data stewards, drives accountability, and supports the organization&rsquo;s vision for data democratization, actionable insights, and predictive analytics.

The Data Governance Lead reports to the Vice President of Insights and Innovation.

Essential Functions

Data Governance Framework Development
<ul>
<li>Design and implement a data governance framework that establishes clear standards, policies, and processes for data management, supporting a single source of truth and predictive analytics.</li>
<li>Partner with the VP of Insights and Innovation and Data Product Owner to align governance with organizational goals.</li>
<li>Establish and lead a Data Governance Council to drive alignment, accountability, and adoption of governance policies across business and IT stakeholders.</li></ul> 


Data Steward Empowerment
<ul>
<li>Define roles, responsibilities, and training for data stewards, enabling accountability for data quality, usage, and compliance.</li>
</ul>
Standard Setting
<ul>
<li>Develop and enforce data standards, including naming conventions, formats, metadata management, and quality metrics.</li>
</ul>
Data Cleanup &amp; Reformatting
<ul>
<li>Lead efforts to assess and reformat existing data to align with governance standards and modern platforms.</li>
</ul>
Compliance &amp; Risk Management
<ul>
<li>Ensure adherence to financial industry regulations and partner with Information Security to mitigate risks related to data security, privacy, and compliance.</li>
</ul>
Agile Collaboration
<ul>
<li>Work within an agile pod to integrate governance practices into data product development, supporting member journey frameworks and predictive analytics.</li>
</ul>
Data Quality Assurance
<ul>
<li>Implement processes for data profiling, validation, and cleansing to support actionable insights and accurate performance measurement.</li>
</ul>
Stakeholder Engagement
<ul>
<li>Collaborate with business units, IT, and other stakeholders to communicate governance policies and promote a culture of data accountability.</li>
<li>Collaborate closely with IT and Data Architecture teams to ensure governance standards align with technical architecture and enterprise data strategies.</li></ul> 


Data Democratization Support
<ul>
<li>Ensure governance supports simplified, accessible data structures for business users.</li>
</ul>
Continuous Improvement
<ul>
<li>Monitor industry trends and refine the governance framework to support the shift from static reporting to predictive analytics.</li>
</ul>
Documentation &amp; Training
<ul>
<li>Maintain documentation of governance policies and provide training to ensure consistent adoption and compliance.</li>
</ul>
Other
<ul>
<li>Adhere to all company policies, procedures and business ethics codes.</li>
<li>Complete required regulatory training as assigned.</li>
<li>Maintain strict adherence and compliance to all laws, rules, regulations, and internal controls specific to the role, including but not limited to Bank Secrecy Act, Anti-Money Laundering, USA Patriot Act, OFAC and Fair Lending regulations.</li></ul> 


Knowledge/Skills/Abilities
<ul>
<li>Excellent communication skills, able to translate governance policies for business and technical teams across all levels of leadership within the organization.</li>
<li>Strong understanding of data governance principles: data quality, metadata management, data lineage, and compliance.</li>
<li>Familiarity with Python or similar scripting languages for data profiling and quality checks.</li>
<li>Experience with data governance tools (Collibra, Alation, Informatica, Purview) and platforms (Databricks, cloud environments).</li>
<li>Proficiency in SQL or similar tools for data profiling and quality assurance.</li>
<li>Leadership and collaboration skills for agile environments.</li>
<li>Analytical mindset to identify gaps and propose solutions.</li>
<li>Ability to manage complex projects in a fast-paced environment.</li>
<li>Ability to change mindset, be a thought partner in driving a data culture.</li>
<li>Ability to establish data governance across the organization to drive member impact.</li></ul> 


Competencies
<ul>
<li>Demonstrating Member Obsession</li>
</ul><ul><li>Puts themselves in the Member&rsquo;s shoes</li>
<li>Looks for friction points</li>
<li>Makes it personalized and easy</li>
</ul><ul><li>Demonstrating Performance Excellence</li>
</ul><ul><li>Sets standards for elevating excellence</li>
<li>Ensures elevated quality</li>
<li>Takes responsibility</li>
<li>Conducts continuous improvement</li>
</ul><ul><li>Demonstrating Innovation</li>
</ul><ul><li>Challenges current thinking</li>
<li>Approaches change with a positive mindset</li></ul> 


Experience

Minimum Qualifications
<ul>
<li>Bachelor&rsquo;s degree in Data Management, Information Systems, Business Administration, or related field.</li>
<li>5+ years in data governance, data management, or related role, with a focus on governance frameworks.</li>
<li>Hands-on experience working with enterprise data warehouses, preferably cloud-based.</li>
<li>Proven experience leading data cleanup or reformatting initiatives.</li>
<li>Experience in agile environments and cross-functional collaboration.</li>
<li>2+ years in financial services (banking, insurance, fintech).</li></ul> 


Preferred Qualifications
<ul>
<li>Master&rsquo;s degree</li>
<li>Certified Data Management Professional (CDMP) or equivalent.</li>
<li>DAMA Certification 
CIPP/US or CIPM (Privacy certifications)</li>
<li>Certifications in data governance tools or cloud-based data warehousing platforms.</li></ul> 


Physical Demands

The physical demands described are representative of those that an employee must meet, with or without accommodation, to perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Frequent
<ul>
<li>While performing the duties of this job, the employee is regularly required to sit; use hands to finger, handle or feel; reach with hands and arms; and talk or hear.</li>
<li>Specific vision abilities required by this job include close vision, distance vision, peripheral vision and ability to adjust focus.</li>
<li>Extensive use of the telephone and virtual communications platforms, requiring the ability to effectively listen and accurately explain complex information.</li></ul> 


Work Environment

The work environment characteristics described are representative of those an employee encounters while performing the essential functions of this job.
<ul>
<li>This position requires frequently working onsite at UFCU Plaza in Austin, Texas.</li>
<li>This position may involve periodic stressful conditions.</li>
<li>May occasionally require an adjusted work schedule, overtime, and evening/weekend hours.</li>
<li>Public contact position, requiring appropriate professional appearance.</li>
<li>Frequent computer use at a workstation up to two hours at a time.</li>
<li>The noise level in the work environment is usually quiet.</li>
</ul>
#INDUFCU
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities 
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.</div>

Data Governance Lead

Salesforce

<div>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Software Engineering
Job Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
Position Overview
We are seeking an experienced Lead Data Scientist (LMTS) to drive data science innovation in predictive modeling and AI within Salesforce&rsquo;s infrastructure domain. As a technical leader, you will design, deploy, and operationalize advanced forecasting and anomaly detection models at scale. You will also shape the roadmap for integrating foundation models and LLMs into production forecasting workflows, enabling faster root cause analysis, proactive recommendations, and automated insights for stakeholders across capacity, cost, and infrastructure planning.
This is a hands-on technical leadership role: you will not only build models but also set technical direction, mentor other data scientists, and raise the bar for reproducibility, scalability, and explainability across our platform.
Responsibilities
<ul><li>Lead the design, development, and deployment of high-impact forecasting models used across capacity planning, FinOps, and infrastructure cost management.
</li><li>Partner with cross-functional leaders (capacity planners, finance, engineering) to shape requirements, influence priorities, and ensure models solve real-world infrastructure challenges.
</li><li>Act as a multiplier on the team by mentoring SMTS/MTS data scientists, providing technical coaching, and instilling best practices in reproducibility, CI/CD, monitoring, and model lifecycle management.
</li><li>Drive the adoption of LLMs and foundation models in applied infrastructure management &mdash; defining architectures, guiding experimentation, and leading integration into production workflows.
</li><li>Own end-to-end quality of deliverables, ensuring models are accurate, robust, observable, and aligned with trust and security standards.
</li><li>Contribute to the broader data science community at Salesforce by sharing methodologies, influencing platform standards, and reviewing technical designs across teams.
</li><li>Champion continuous improvement in data science processes, proactively addressing tech debt, standardizing pipelines, and defining metrics (SLIs/SLOs) to measure forecast performance. 
 
 
</li></ul>Qualifications
<ul><li>Advanced technical degree in a relevant field (Computer Science, Statistics, Operations Research, Applied Math, etc.).
</li><li>8+ years of industry experience building and deploying machine learning solutions (time series forecasting experience strongly preferred).
</li><li>Proven ability to lead technical direction for data science projects, mentor junior members, and influence cross-team engineering practices.
</li><li>Demonstrated success delivering production-grade ML/AI systems in cloud environments (AWS/GCP), including monitoring, CI/CD, and observability.
</li><li>Strong expertise in time series forecasting and ML methods; familiarity with foundation models and LLMs in applied data science.
</li><li>Proficiency in Python and modern DS/ML tools (mlFlow, Airflow, Docker, Spark, SQL, Pandas/Sklearn).
</li><li>Strong communicator, capable of influencing both technical and non-technical stakeholders, and of synthesizing complex data science concepts into actionable insights.
</li><li>Track record of driving measurable business impact through data science solutions at scale.
</li></ul>BENEFITS &amp; PERKS
<ul><li>Comprehensive benefits package including well-being reimbursement, generous parental leave, adoption assistance, fertility benefits, and more!
</li><li>World-class enablement and on-demand training with Trailhead.com
</li><li>Exposure to executive thought leaders and regular 1:1 coaching with leadership
</li><li>Volunteer opportunities and participation in our 1:1:1 model for giving back to the community
</li><li>For more details, visit https://www.salesforcebenefits.com/
</li></ul>Unleash Your Potential
When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
Accommodations
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Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.</div>

Lead Data Scientist | LMTS

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