Main Responsibilities and Required Skills for Data Architect
A Data Architect is responsible for defining, developing, and maintaining effective and efficient data architecture and data ownership. They work closely with programming staff on Data Architecture and Infrastructure to meet business requirements. In this blog post we describe the primary responsibilities and the most in-demand hard and soft skills for Data Architects.
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Main Responsibilities of Data Architect
The following list describes the typical responsibilities of a Data Architect:
Address
Address data related problems in regards to systems integration and compatibility.
Advise
Advise and track new developments as part of our 3-5 year strategic roadmap.
Align
Align technical approaches across the engineering teams.
Analyze
Analyze and resolve problems.
Analyze source system data and create mappings using business rules to transform data.
Apply
Apply lean thinking and tools to identify and eliminate waste in all areas of the position.
Architect
Architect complex data models that support the scaleable transfer of data to / from multiple systems.
Articulate
Articulate and advocate industry and department best practices.
Articulate architecture pros & cons with customer technology leads.
Assess
Assess data curation requirements and propose remediation approach.
Assist in
Assist in system integration by modelling data from legacy systems prior to migration.
Assist with the development and enforcement of methodologies and standards for data modeling.
Attend
Attend and participate in all assigned meetings.
Attend Architecture Meeting.
Automate
Automate testing, including unit tests and Cypress or Selenium tests.
Brainstorm
Brainstorm use-cases and articulate value levers for driving further adoption.
Build
Build and develop expertise to key technology trends and make this expertise available to clients.
Build constructive and effective relationships.
Build, lead, manage, and direct a team of data architects within enterprise architecture team.
Build relationships and become a trusted advisor for customers.
Capture
Capture on-going enhancements to scope of services for existing clients as needed into roadmap.
Champion
Champion Data as an Asset design with business and development teams.
Coach
Coach and educate more junior members of your team in quality technical delivery.
Collaborate with
Collaborate with application development teams to surface data solutions for all programs.
Collaborate with peers to ensure requirements are understood and a high quality product results.
Collaborate with project managers and business leaders for all projects involving enterprise data.
Collaborate with project managers and business leaders for all projects involving enterprise data.
Collaborate with stakeholders to build data models that support new products and features.
Communicate
Communicate the technical design and work closely with development team.
Conduct
Conduct and support data analysis, data mining, and identify patterns.
Consult
Consult and advise engineers, analysts, architects, managers and executives.
Consult, collaborate, and recommend solutions for batch and streaming use case patterns.
Contribute to
Contribute to formulation of architecture strategy for EMEA BI practice and for Warsaw delivery hub.
Coordinate with
Coordinate with the Data Science department to identify future needs and requirements.
Coordinate with the Integration department to identify future needs and requirements.
Create
Create detailed design specifications to map source system data assets to the physical data model.
Create reference architecture frameworks and patterns.
Create structure and queries using AWS Athena.
Define
Define and manage and master data management strategy for cloud-based data sets.
Define out logical global data model and work with the engineers to implement this.
Define technical roadmaps that align the product deliverables.
Define the data requirements and structure for the application.
Define the operational processes to deliver consistent value to merchants and partners.
Deploy
Deploy and manage on-premise or cloud-based data products and platforms.
Design
Design and deliver the Enterprise Commercial Data Architecture Model.
Design and implement a data governance strategy across the organization.
Design and implement data encryption and tokenization solutions.
Design and implement migration plan for existing data, as needed.
Design and implement sharding and indexing strategies for MongoDB.
Design and provide support to all data management methodologies according to required standards.
Design APIs and Frameworks for reuse.
Design data storage, movement and orchestration solutions.
Design long-term, reliable, and end-to-end technical architectures.
Design mapping of data from source to target systems.
Design short term solutions to achieve immediate goals while preparing a long-term data roadmap.
Determine
Determine database structural requirements by analyzing business operations and applications.
Determine the fit for purpose data store / database to persist the data in the cloud.
Develop
Develop a framework for managing schemas and for handling schema evolution across our platform.
Develop a model management and repository strategy to manage all information architecture artifacts.
Develop and maintain effective and efficient data architecture and data ownership.
Develop and manage data processes to ensure that data is available and usable.
Develop a roadmap to meet cross functional data needs, building shared goals and project plans.
Develop close collaboration with senior analysts and data owners across multiple business domains.
Develop custom predictive models and algorithms using AI and Machine Learning.
Develop data quality control and remediation plan.
Develop real time system analytics to improve overall reporting efficiency.
Develop new benchmarks and tools for Data performance measurement and capacity.
Develop overall data strategy with full governance and master data.
Develop Proof-of-Concept projects to validate new architectures and solutions.
Develop reference architecture and identify and document data flows.
Develop reporting and analytical data models to meet the needs of the organization.
Drive
Drive refinements to our data transformation processes.
Drive projects to completion.
Drive the vision to build standards around data governance, data security, privacy, and data quality.
Educate
Educate customer on Cloud technologies and influence direction of the solution.
Enable
Enable, mentor and coach colleagues in Data Architect capabilities and technologies.
Encourage
Encourage and assist in operational use of data for business process functions.
Enhance
Enhance batch routines by optimizing for more modern near real-time capabilities.
Ensure
Ensure CMS data and data management standards are met and maintained.
Ensure compliance with company polices, audit requirements and data privacy regulations.
Ensure our Data Acquisition strategy moves towards an Integrated EDW.
Ensure solutions meet the compliance and security needs of TR.
Ensure technology solutions are in alignment with data architecture principles and target state.
Ensure that risks associated with deployment are adequately understood and documented.
Ensure that the Data Architecture solution supports the Technology Architectural point-of-arrival.
Ensure the implementation of agreed architecture and infrastructure.
Ensure the quality of all technical outputs meets expectations.
Establish
Establish standards for data management.
Estimate
Estimate effort for design and delivery of tasks.
Evaluate
Evaluate data models at all levels including conceptual, logical, and physical.
Evaluate products for project and future usage and take responsibility for trialing new technologies.
Evaluate reusability of current data for additional analyses.
Execute
Execute data cleanings operations using technical tools, common sense, and industry best practices.
Exemplify
Exemplify our Guiding Principles of partnership, integrity and high performance.
Expand
Expand several existing investment domain specific data designs to do likewise.
Explore
Explore new ways of conducting business and organisational processes.
Facilitate
Facilitate business workshops to define, design, and document analytics data needs.
Focus
Focus on establishing the architecture, design, and security of various databases.
Follow
Follow engineering best practices and cultivate a best-practices culture.
Gather
Gather metadata, analyzes and identifies data sources and profiles data.
Handle
Handle the most complex issues and problems.
Help
Help maintain the integrity and security of the company database.
Help prepare cost estimates.
Help the Data Architecture Practice Lead in establishing and refining the data architecture practice.
Identify
Identify and explore new business areas and opportunities enabled by data analytics.
Identify gaps and recommend solutions within current ETL architecture.
Identify generic solution patterns to reduce complexity and cost of development.
Identify, monitor, and recommend sources of vendor data.
Identify application patterns and analytics in support of better service level objectives.
Identify new data queries and definitions across platforms and industries.
Implement
Implement a strategy for monitoring user platform adoption and data quality and retention.
Include
Include data design, database architecture, metadata and repository creation.
Influence
Influence / recommend ways to improve data reliability, efficiency and quality.
Initiate
Initiate and drive data management initiatives across the application landscape.
Install
Install and organize information systems to guarantee company functionality.
Keep
Keep in touch with new tools, technologies and improvements.
Know
Know how to get things done both through formal channels and the informal network.
Lead
Lead cloud engagements for migrating client environments to the Magento Cloud.
Lead technology teams during complex project delivery.
Lead the execution of operational programs.
Like
Like the importance of data security and data governance.
Maintain
Maintain and modify existing applications and corresponding documentation.
Maintain metrics on data quality and accuracy.
Maintain secure data solutions in accordance to privacy laws, security and compliance controls.
Make
Make a difference in the lives of thousands of students as they explore educational opportunities.
Manage
Manage Data Analytics and BI implementation.
Manage portfolio of product data set backlog and support prioritization to ensure alignment with MDM.
Manage the adoption of appropriate big data and data warehousing technologies and platforms.
Meet
Meet with business and technology leaders, presenting data topics.
Mentor
Mentor team members and acts as a technical lead for less senior team members.
Model
Model and design the application data structure, storage and integration.
Monitor
Monitor and identify appropriate software, tools and systems to achieve all data technology goals.
Monitor data quality and identify data anomalies and assess possible business impact.
Optimize
Optimize performance of queries and ELT / ETL procedures.
Oversee
Oversee and manage the design of the organization's evolving data architecture.
Oversee and monitor all frameworks / platforms moving data across BCAA repositories.
Oversee end-to-end data life cycle management activities.
Oversee handover to operational teams.
Oversee our existing database system, optimising and upgrading where necessary.
Oversee all documentation and deliverables related to data architecture and implementation.
Oversee the maintenance of the data from source to marketing activation.
Oversee the mapping of data sources, data movement, interfaces, and analytics.
Oversee the migration of data from legacy systems to Azure data platforms.
Own
Own data warehouse plans for a product or a group of products.
Participate in
Participate in architecting and evolving CMT's future data storage framework.
Participate in data strategy and roadmap exercises.
Participate in SQL development reviews (ad hoc scripts, stored procedure, triggers etc.).
Participate in troubleshooting and performance optimization where required.
Participate in troubleshooting and performance optimization with the BI and Data Engineering teams.
Perform
Perform and / or lead project data consultants in dry run data load testing.
Perform offline analysis of large data sets using components of a big data software ecosystem.
Perform root cause analysis and tracks resolution of data quality issues.
Plan
Plan, set up and execute business and technology initiatives to fulfil analytics data needs.
Prepare
Prepare documents for data architecture and maintain knowledge on large data structures as well.
Prepare specifications to drive development and assist with test case creation.
Produce
Produce conceptual and logical data models and flowcharts.
Produce technology roadmaps in support of SI's application portfolio vision and strategy.
Promote
Promote an understanding of Data Architecture across the organisation.
Promote best practices for data management.
Promote data governance, quality and security across the enterprise.
Provide
Provide advice and guidance to assigned Group / Functions on implementation of solutions.
Provide assistance for creating models / objects within our Data Visualization software (Looker).
Provide business architecture and systems processing guidance.
Provide consultation regarding OCIO data center migration action plans, efficacy, timelines, etc..
Provide guidance and basic principles to projects to assist efficient management of data assets.
Provide guidance, consultation and support on building out a new Data Architecture platform.
Provide guidance in effective migration of data from legacy systems to modern data platforms.
Provide leadership and guidance with enterprise data strategies.
Provide operational support for Management Information Systems.
Provide strong leadership for implementing best business practices in the data field.
Provide subject matter expertise and technical leadership on the data architecture discipline.
Provide technical guidance in platform development and platform-wide solutions.
Provide technical mentoring.
Provide timely and accurate status reports as necessary.
Recommend
Recommend and implement best practices for data management and governance.
Recommend and lead roadmaps and component programs.
Recommend solutions to improve new and existing database systems.
Reconcile
Reconcile multiple data sources and data models into a single, logically consistent model.
Review
Review existing mappings and build procedures for translating seed mappings into SQL.
Secure
Secure and automate solutions through collaboration with InfoSec and Engineering resources.
Secure bike storage with showers and towel service.
Set
Set high standards and goals.
Solve
Solve technical problems, simple and complex, in a lean and efficient manner.
Stay close to
Stay close to industry best practices in account, client data and KYC management.
Support
Support APIs & integration management, versions and releases.
Support clients problem solve and deal with issues that arise.
Support conceptual and logical data modeling efforts for strategic initiatives.
Support on-going enhancements to scope of services as needed.
Support project teams and interface with clients.
Support solution architects to architect and deliver solutions.
Support the clients and partners regarding SPM data model.
Support the Design and Build of Analytical solutions using DataBricks, AWS.
Support the VP Data Management and Operations as needed.
Support with establishing and developing best practice within Data Architecture and Infrastructure.
Test
Test programs or databases, correct errors and make necessary modifications.
Understand
Understand the reasoning behind key policies, practices and procedures.
Understand user needs and design the best technical solution to meet them.
Update
Update, evolve, and implement existing Data Warehouse Roadmap, incorporating new business needs.
Use
Use of microservice architectures in production.
Work with
Work closely with programming staff on database design changes to meet business requirements.
Work closely with technical team on what technologies are to be utilized within any given solution.
Work cross-functionally with the marketing team on campaigns and initiatives.
Work / Life Balance time off programs.
Work on new product evaluation, certification, defining standards for tool fitment to the platform.
Work with Business System Analyst to translate requirements into functional specifications.
Work with complex Data modeling and design patterns for BI / Analytics reporting requirements.
Work with engineering teams to build scalable data stores with business-centric data management.
Work with product managers to research and propose solutions to business problems.
Most In-demand Hard Skills
The following list describes the most required technical skills of a Data Architect:
Data Modeling
Java
Design
Tableau
Kafka
Big Data
Data Architect
Data Warehousing
Hive
Oracle
Cloud
Informatica
Data Management
Relational
Designing
Data Warehouse
Snowflake
Architecture
GCP
Redshift
Scala
SQL Server
Business Intelligence
Data Integration
Data Analysis
Information Systems
Data Engineering
Mysql
Nosql
Data Governance
Implementation
Big Data Technologies
Data Science
Machine Learning
Architecting
Data Modelling
Data Mining
Most In-demand Soft Skills
The following list describes the most required soft skills of a Data Architect:
Written and oral communication skills
Analytical ability
Problem-solving attitude
Interpersonal skills
Organizational capacity
Presentation
Attention to detail
Collaborative
Leadership
Proactive
Customer focused
Influencing
Self-motivated
Team player
Facilitation
Self-starter
Multi-task simultaneous different customer projects
Negotiation
Self-managed
Work independently with little direction
Accurate
Critical thinker
Decision-making skills
Time-management
Creative
