Data Architect II

Description

Expectations from this role:
Proficiency: Design, develop and implement data architecture for a large enterprise from Data Ingestion to Data Consumption

Outcomes:

1.    Architect, design and implement high performance large volume data integration, transformation, warehouse, data lakes, data in cloud, data analysis, reporting and visualization of data from data warehouse using any one tool like (PowerBI, Tableau, D3 etc)
2.    Design and implement any one of cloud big data solutions (AWS/AZURE/GCP) along with deep understanding in Apache Hadoop and Apache tools like sqoop, flume, spark, kafka, hive, pig, etc.
3.    Design and implement data analysis solutions involving cost optimization, patterns, prediction and deriving inference from data. This can either AI or any statistical model or using graph models (tools like Lucene, Gephi)
4.    Design and implement data virtualization (Dendo) and/or integrate with platforms specific to data service/data science areas such as Fire, Mcheck
5.    Plan information architecture by studying the site concept, strategy, and target audience; designing information structure, work-and dataflow, and navigation. An expert in any one domain (Retail, Healthcare, Banking & Financials, etc); evaluating information representation, backup, recovery and security specifications
6.    Customer focus – understand customer problem and provide solutions to customer, building trust. Able to run workshops for customer in data services area, create data strategy for customer and able to present solutions, concepts and strategy to customer
7.    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
8.    Participation in external seminars as a speaker, publish white paper or apply for patentsTypical performance measures:
6.    Percent of time spent in a year to develop for customer an architecture or strategy for data
7.    Percent of time spent in solving customer problem in data area
8.    Percent of time spent for provide data strategy for customer
9.    Dollar value of RFP’s won for which solutioning was proposed
10.    Dollar value saved for customer using cost reduction or dollar value created for customer by prediction models by you or your teamPerformance Areas:
1.    Strategy & Planning:
a)    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.
b)    Create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap.
c)    Establish processes for governing the identification, collection, and use of corporate data assets and metadata; take steps to assure metadata accuracy and validity.
d)    Establish methods and procedures for tracking data quality, completeness, redundancy, and improvement.
e)    Ensure that data strategies and architectures meet regulatory compliance requirements.
f)    Engage external stakeholders including standards organizations, regulatory bodies, operators, and scientific research communities.
g)    Ensure business needs in operational data, reporting data are met
h)    Advising business on models that can be used for optimization and prediction

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

3.    Project Control and Review
a)    Perform data architecture design review
b)    Identify opportunities for optimization of cost, time and asset utilization in complex projects and advise relevant teams accordingly where possible
c)    Provide advice to teams facing complex technical issues in the course of project delivery
d)    Conduct planned and unplanned technical audits for complex projects as applicable
e)    Define and measure project /program specific architectural and technology quality metrics

4.    Knowledge Management & Capability Development
a)    Provide inputs to teams for training, etc.
b)    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
c)    Gain and cultivate domain expertise to provide best and optimized solution to customer

5.    Requirement gathering and Analysis
a)    Understand the requirements from a larger system / transformation program context
b)    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 areas for joint GTM with the partner
    Identify alliance partners based on the understanding of service offerings and client requirements
    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

6.    Technology Consulting
a)    Define problem statement for the customer
b)    Analyse application/ technology landscape, process, tools and arrive at the solution options best fit for the client
c)    Analyse Cost Vs. Benefits of solution options
d)    Define the technology/ architecture roadmap for the client
e)    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, and 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
    Create IP for the organization

7.    Sales Support and Project Estimation
a)    Develop collaterals for proposals
b)    Conduct workshops at the client site to assist the sales team in sales support, if required
c)    Compare various designs and propose appropriate technology solutions based on the understanding of the RFP and inputs from Architects
d)    Calculate and present estimates based on high level designs to management for supporting go/ no-go decisions
e)    Review estimations and resource plan
f)    Review risk and mitigation plan
g)    Anchor proposal development with cross-linkages across multiple competency units to arrive at a coherent solution, unique value propositions and clear differentiator
h)    Participate in client presentation and client visits

8.    Data Design & Definition
a)    Ensure alignment of the high-level architecture with the existing client need and business logic / review design prepared by architects
b)    Ensure the involvement of appropriate teams in data design
c)    Ensure technical integrate ability, requirements compliance of the solution, especially in case of a multi group / multi-vendor program
d)    Involve external partners / horizontals as appropriate
e)    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
f)    Ensure UST architecture principles and QOA (Quality of Architecture) are maintained. Analyse trade-offs and provide recommendations, if any, on the data architecture
g)    Identify opportunities for efficiency improvements.
h)    Understand the various work streams and the technologies necessary to deliver on large programs
i)    Resolve any issues based on industry expertise / partners leverage
j)    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

9.    Project Management Support
a)    Proactive identification and management of technical risks

10.    Stakeholder Management
a)    Build credibility with the client as a technical go-to person
b)    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
    Development of business case for investments for approval from management
    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 GTMa)    Skill Examples:
1.    Use knowledge of Technology Trends to provide inputs on potential areas of opportunity for UST. Provide inputs to the specialist on creation of technology roadmap for the client, research on new products / trends / best practices
2.    Use knowledge of Architecture Concepts and Principles to create architecture catering to functional and non-functional requirements. Re-engineer existing architecture solutions, provide training on best practices in architecture and create data migration strategy for customer
3.    Use knowledge of Knowledge Management Tools & Techniques to leverage existing material/ re-usable assets in knowledge repository. Independently create and update knowledge artefact. Create and track project specific KT plans. Provide training to others, write white papers/ blogs at internal level, write technical documents
4.    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
5.    5.Use knowledge to design big data solutions for customer, hosted in cloud, provide pros and cons of various tools in big data solution to customer, provide pros and cons of cloud solutions, do cost optimization of cloud solutions
6.    Use knowledge to design data analysis solution involving structure and non-structure data, pattern analysis using AI & ML/ Graph, prediction and cost optimization algorithm
7.    Use knowledge to respond to RFP in effective way covering all areas of data service from ingestion to consumption
8.    Use knowledge to define Data Strategy for customer
9.    Strong proficiencies in understanding data, workflows and dataflows
10.    Attention to details
11.    High Analytical capabilities
12.    Creativity in developing solutions
13.    Self-learning
14.    Resilience in solving problemsKnowledge Examples:
1.    Domain knowledge, understanding domain data
2.    Applied Mathematics and Statistics
3.    Well versed in English language - verbal and written
4.    Skilled in writing design documents, usage of Power Point, Visio
5.    Data visualization, streaming
6.    Data migration
7.    Data modelling, vector and Graphs
8.    RDMSs (relational database management systems), SQL.
9.    Databases such as NoSQL and cloud computing.
10.    Hadoop technologies, like MapReduce, Hive, and Pig.
11.    Programming languages, especially Python and Java
12.    Operating systems, including UNIX and MS Windows
13.    Cloud providers
14.    Backup/archival software
15.    Leading data security practices
16.    Industry data platforms, trends