Role Proficiency:

Design develop and implement data architecture for a large enterprise in two of the following: Data ingestion Data Management Data Delivery Data Consumption.

Outcomes:

     Architect design and implement high performance large volume data integration transformation warehouse data lakes data in cloud or large volume warehouse data in cloud data analysis reporting and visualization of data from data warehouse using any one tool like(PowerBI Tableau D3 etc)      Design and implement any one of cloud big data solution (AWS/AZURE/GCP/Apache Hadoop)      Plan information architecture by studying the site concept strategy domain and target audience; information structure and features designing information structure evaluating information representation backup recovery and security specification      Customer focus – improves customer service effectively engages customers build with customer on your solution capability.      Provide end-to-end technical guidance and roadmaps for Sales & Marketing      Validate estimates from team      Hold certification in Architect/Big Data specialty certification in one of AWS or Azure or GCP with experience in knowledge of other architecting Big Data solutions on other cloud and Big Data platforms

Measures of Outcomes:

     Percent of time spent in a year to develop for customer an architecture or strategy for data      Percent of time spent in solving customer problem in data area      Percent of time spent for provide data strategy for customer      Dollar value of RFP’s won for which solutioning was proposed Dollar value saved for customer using cost reduction or dollar value created for customer by prediction models by you or your team

Outputs Expected:

Strategy & Planning:

Develop and deliver long-term strategic goals for data architecture vision and standards in conjunction with data users
department managers
clients
and other key stakeholders Create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap Establish processes for governing the identification
collection
and use of corporate data assets and metadata; take steps to assure metadata accuracy and validity Establish methods and procedures for tracking data quality
completeness
redundancy
and Improvement Ensure that data strategies and architectures meet regulatory compliance requirements Engage external stakeholders including standards organizations
regulatory bodies
operators
and scientific research communities Ensure business needs in operational data
reporting data are met

Operational Management :

Establish governance
stewardship
and frameworks for managing data across the organization Develop and promote data management methodologies and standards Select and implement the appropriate tools
software
applications
and systems to support data technology goals Collaborate with project managers and business teams for all projects involving enterprise data Address data-related issues with systems integration
compatibility
and multi-platform integration Act as a leader and advocate of data management
including coaching
training
and Develop and implement key components as needed to create testing criteria in order to guarantee the fidelity and performance of data architecture Document the data architecture and environment in order to maintain a current and accurate view of the larger data picture Identify and develop opportunities for data reuse
migration
or retirement

Project Control and Review :

Perform data architecture design review Identify opportunities for optimization of cost
time and asset utilization in complex projects and advise relevant teams accordingly where possible Provide advice to teams facing complex technical issues in the course of project delivery Conduct planned and unplanned technical audits for complex projects as applicable Define and measure project and program specific architectural and technology quality metrics

Knowledge Management & Capability Development :

Provide inputs to teams for training
etc. Identify the training needs and conduct internal sessions to meet the same Partner with UST Gamma to Create curriculum
assessments
training programs
courseware based on new service offerings and solutions etc. Update collateral on to the knowledge management repository Gain and cultivate domain expertise to provide best and optimized solution to customer

Requirement gathering and Analysis:

Understand the requirements from a larger system / transformation program context Validate the cross application / cross technology requirements to ensure integrate ability and reconciliation of conflicting requirements
by working with customers and other stakeholders

People Management:

Provide support to various project managers in identification of training needs of the team Conduct training / certifications with the help of Gamma and mentoring with respect to technical skills on projects Support technical evaluation of external and internal candidates to meet project requirements Perform career guidance and performance management for team members

Alliance Management:

Identify alliance partners based on the understanding of service offerings and client requirements. Identify areas for joint GTM with the partner Develop internal capabilities/complementary toolsets to support the GTM strategy Maintain the relationship with partners Act as the UST technical POC for the specific technology/solution area

Technology Consulting:

Define problem statement for the customer Analyse application/ technology landscape
process
tools and arrive at the solution options best fit for the client Analyse Cost Vs. Benefits of solution options Define the technology/ architecture roadmap for the client Articulate the cost vs. benefits of options to key stakeholders in customer

Innovation and Thought Leadership:

Participate in external forums (seminars
paper presentation
etc.) Interact and engage with customers/ partners around new innovative ideas
concepts
assets; as well as industry trends and implications Participate in Beta testing of products / joint lab setup with customer to explore application of new technologies / products Identify areas where components/accelerators or design patterns could be reused across different accounts Create documents
reports
white papers (international/national) on the research findings

Sales Support and Project Estimation:

Develop collaterals for proposals Compare various designs and propose appropriate technology solutions based on the understanding of the RFP and inputs from Architects Calculate and present estimates based on high level designs to management for supporting go/ no-go decisions Review estimations and resource plan Review risk and mitigation plan Participate in client presentation and client visits

Data Design & Definition:

Ensure alignment of the high-level architecture with the existing client need and business logic / review design prepared by architects Ensure the involvement of appropriate teams in data design Ensure technical integrate ability
requirements compliance of the solution
especially in case of a multi group / multi-vendor program Involve external partners / horizontals as appropriate Provide guidance to the team around the usage of data architecture and experience in solution implementation
product selection and definition
configuration
migration and transformations between cloud and hosted solutions. Take responsibility for developing cutting edge wallet applications Ensure UST architecture principles and QOA (Quality of Architecture) are maintained. Analyse trade-offs and provide recommendations
if any
on the data architecture Identify opportunities for efficiency improvements. Understand the various work streams and the technologies necessary to deliver on large programs Resolve any issues based on industry expertise / partners leverage Provide best in class technology and solution options to customers with detailed examples and case studies. Guide customer on process and technology improvements to achieve agility and quick results

Project Management Support:

Proactive identification and management of technical risks

Stakeholder Management:

Build credibility with the client as a technical go-to person Work to expand professional network in the client organization

New Service Design:

Identify potential opportunities for new service offerings based on customer voice/ partner inputs / industry connects and trends Support the development of business case for investments for approval from management Work with partners to co-develop a joint GTM (as applicable) Develop IP/tools and framework to address the opportunity technically Lead beta testing / POC as applicable Develop collaterals
guides for GTM

Skill Examples:

     Use knowledge of technology trends to provide inputs on potential areas of opportunity for UST      Use knowledge of Architecture Concepts and Principles to create architecture catering to functional and non-functional requirements under guidance of the specialist. Re-engineer existing architecture solutions under the guidance of the specialist. Provide training on best practices in architecture under guidance      Use independent knowledge of Design Patterns Tools and Principles to create high level design for the given requirements. Evaluate multiple design options and choose the appropriate options for best possible trade-offs. Conduct knowledge sessions to enhance team's design capabilities. Review the low and high level design created by Specialists for efficiency (consumption of hardware memory and memory leaks etc.) and maintainability of design      Use knowledge of Software Development Process Tools & Techniques to identify and assess incremental improvements for software development process methodology and tools. Take technical responsibility for all stages in the software development process. Conduct optimal coding with clear understanding of memory leakage and related impact. Implement global standards and guidelines relevant to programming and development come up with 'points of view' and new technological ideas      Use knowledge of Project Management & Agile Tools and Techniques to support plan and manage medium size projects/programs as defined within UST; identify risks and mitigation strategies      Use knowledge of Project Metrics to understand relevance in project. Collect and collate project metrics and share it with the relevant stakeholders      Use knowledge of Estimation and Resource Planning to create estimate and plan resources for specific modules / small projects with detailed requirements or user stories in place      Use knowledge of Knowledge Management Tools & Techniques to leverage existing material/ re-usable assets in knowledge repository. Independently create and update knowledge artefacts. Create and track project specific KT plans. Provide training to others write white papers/ blogs at internal level write technical documents/ user understanding documents at the end of the project      Use knowledge of Technical Standards Documentation & Templates to create documentation appropriate for the project needs. Create documentation appropriate for the reusable assets/ best practices/ case studies   Use knowledge of Requirement Gathering and Analysis to support creation of requirements documents or user stories and high level process maps. Identify gaps on the basis of business process analyse responses to clarification questions and produce design documents. Create and review estimates and solutions at project level/program level. Create and review design artefacts update resourcing and schedule based on impacted areas identified. Create design specifically for the non-functional requirements   Strong proficiencies in understanding data workflows and dataflows   Attention to details   High Analytical capabilities   Creativity in developing solutions   Self-learning   Resilience in solving problems

Knowledge Examples:

     Domain knowledge understanding domain data      Applied Mathematics and Statistics      Skilled in writing design documents usage of Power Point Visio      Data visualization streaming      Data migration      Data modelling vector and Graphs      RDMSs (relational database management systems) SQL      Databases such as NoSQL and cloud computing      Hadoop technologies like MapReduce Hive and Pig   Programming languages especially Python and Java   Operating systems including UNIX and MS Windows   Cloud solutions   Backup/archival software   Understanding of data security

Additional Comments:

Job Title: Lead Data Quality Engineer (with Cloud-Agnostic Data Engineering Expertise) ________________________________________ Summary We are seeking a highly skilled Lead Data Quality Engineer with a strong foundation in data engineering to lead our data quality and reliability initiatives across modern, cloud-agnostic data platforms. You will drive the strategy, design, and execution of robust data quality frameworks and performance validation processes for large-scale, distributed data systems. The ideal candidate is a hands-on technologist with a passion for clean, accurate, and high-performing data pipelines — and the ability to work across cloud platforms, teams, and tools to ensure data trustworthiness across the enterprise. ________________________________________ Key Responsibilities Data Quality & Performance Engineering (Primary Focus) • Define, implement, and continuously improve data quality frameworks, validation rules, and monitoring systems across data pipelines and APIs. • Lead performance and reliability testing for data lakes, data warehouses, and streaming systems. • Analyze pipeline and API performance to detect and resolve bottlenecks related to latency, throughput, and reliability. • Integrate and manage tools such as Great Expectations, dbt, JMeter, Locust, Grafana, and Prometheus. • Lead a team of SDETs focused on test automation and data platform QA across environments. • Collaborate with business stakeholders to define data quality KPIs and communicate insights from quality monitoring and performance analysis. • Work closely with Data Engineers and Platform Engineers to embed quality controls into CI/CD pipelines and infrastructure-as-code deployments. Data Engineering & Platform Support (Secondary Focus) • Contribute to the design and development of data ingestion, transformation, and storage processes. • Support scalable ETL/ELT pipelines using best-in-class tools and frameworks. • Ensure data governance, lineage, and compliance across distributed cloud environments. • Collaborate with BI and analytics teams to ensure data availability for dashboards, APIs, and machine learning models. • Contribute to infrastructure automation using tools like Terraform, CloudFormation, or other IaC tools. ________________________________________ Required Qualifications • Bachelor's or Master's degree in Computer Science, Information Systems, or a related field. • 12+ years in commercial software engineering • 5+ years of experience in Data Engineering with a focus on Data Quality, and 2+ years in a lead or senior quality engineering role. • Strong hands-on programming skills in Java, Python, and SQL. • Expertise in test automation tools (e.g., Selenium, REST Assured, Postman, Cypress). • Experience working with relational, NoSQL, and document-oriented databases (e.g., PostgreSQL, MongoDB, Elasticsearch). • Familiarity with big data and distributed processing tools such as Apache Spark, Kafka, Hadoop, etc. • Proven experience in performance engineering of data systems (e.g., tuning for scale and latency). • Hands-on experience with at least one major cloud platform (AWS, Azure, GCP); familiarity with others preferred. • Strong communication and stakeholder engagement skills. ________________________________________ Preferred Qualifications • Certifications in AWS, Azure, or GCP related to Data Engineering or DevOps. • Familiarity with: o Data governance and cataloging tools: Collibra, Apache Atlas, Alation. o Lakehouse systems: Delta Lake, Apache Iceberg, Hudi. o MLOps or DataOps pipelines and platforms (e.g., MLflow, Kubeflow, TensorFlow). • Experience in regulated or domain-specific environments such as Hospitality Domain