Principal Data Architect

Overview

On Site
USD 162,323.00 - 191,594.00 per year
Full Time

Skills

Project Management
Performance Management
Preventive Maintenance
Network
Physical Security
SAP BASIS
IT Strategy
Business Process
System Integration
Data Security
Data Analysis
Data Architecture
Roadmaps
Testing
Business Strategy
Leadership
Data Flow
Data Governance
Data Integrity
Data Migration
Data Quality
Training
PyTorch
Advanced Analytics
Optimization
Scalability
Algorithms
Educate
FOCUS
Privacy
Regulatory Compliance
Deep Learning
Natural Language Processing
Computer Vision
Invoices
Mentorship
Talent Management
Enterprise Architecture
Cloud Architecture
Virtualization
Analytics
Performance Tuning
Capacity Management
Disaster Recovery
Recovery
Risk Assessment
Software Development
Computer Science
Python
R
RESTful
API
Flask
Continuous Integration
Continuous Delivery
Jenkins
Orchestration
PySpark
Pandas
scikit-learn
TensorFlow
XGBoost
Time Series
Design Patterns
Data Science
Relational Databases
Storage
Workflow
Kubernetes
Docker
Google Cloud Platform
Google Cloud
Data Engineering
Machine Learning Operations (ML Ops)
Vertex
Communication
Collaboration
Writing
Critical Thinking
Decision-making
Active Listening
Attention To Detail
Customer Service
Problem Solving
Conflict Resolution
Management
TOGAF
SAS
Information Management
Machine Learning (ML)
Artificial Intelligence
Database
Cloudera
Cisco Certifications
Cloud Computing
Databricks
Oracle
Data Management
Modeling
Microsoft
Microsoft Azure
Amazon Web Services
Big Data
Data Modeling
IBM
Partnership
Innovation
Customer Focus
Customer Relationship Management (CRM)
Law
Finance
FDS
MTA
Military

Job Details

Description

Job Title: Principal Data Architect

Reports To: Sr Director, Enterprise Information & Data Architecture

Salary Range: $162,323 - $191,594

Hay Points: 775

Dept/Div: MTA IT Strategy & Architecture

Location: 2 Broadway, New York, NY 10004 or other locations as required

Hours of Work: 9:00 AM - 5:30 PM (7.5 work hours/day) or various as required

Application Deadline: Open Until Filled

ABOUT US

The MTA transportation network has very large systems and infrastructure for financial, business, automated train, transportation, power, and physical security. The MTA IT Strategy & Architecture is centrally responsible for providing a full range of Information and Operational Technology services to the MTA agencies and administrative units through its operating and support units. Services are provided on a 7/24/365 basis in support of the MTA organization and its ridership.

MTA IT Strategy & Architecture provides enterprise consulting and advisory services in alignment with MTA's business vision to support technology optimization and innovation.

SUMMARY

This role leads the data and artificial intelligence initiatives. This role establishes the design, develops, and implements scalable data solutions that support the MTA's business processes and decision-making. With a strong background in data architecture, machine learning, and cloud technologies, the architect focuses on driving business value through data-driven insights and AI solutions, ensuring seamless system integration, and adhering to best practices in data security and governance.

RESPONSIBILTIES
  • Develop and execute data, analytics, and AI strategy to meet requested needs combined with consideration of the future data architecture strategy. Adds new components to the roadmap and monitors the testing and implementation of changes.

  • Influence and govern current and future architectural blueprints and promote architectural initiatives that improve efficiency and support our business strategy. Ensure that what we do solves both enterprise and local needs.

  • Formulates and promotes the organization's vision for analytics, provides leadership and oversight, and ensures the adoption of the analytics program.

  • Serves as the overall architect for the design and delivery of the analytics program.

  • Collaborate with business stakeholders and IT teams to define and implement a holistic data strategy aligned with MTA's goals.

  • Create and maintain scalable, efficient, and secure logical and physical data models.

  • Oversee the integration of data sources across various platforms, ensuring smooth data flow and high-performance architecture.

  • Establish and enforce data governance policies and frameworks to ensure data integrity, security, and compliance.

  • Lead data migration projects, ensuring minimal disruption and high data quality throughout transitions.

  • Design cloud-based data architectures using platforms like AWS, Azure, or Google Cloud.

  • Develop and execute the organization's AI strategy to drive business innovation and efficiency.

  • Lead the design, development, and deployment of machine learning models to enhance decision-making and automate key processes.

  • Prepare large-scale datasets, ensuring they are clean, structured, and ready for training machine learning algorithms.

  • Implement best practices for the full lifecycle of AI/ML models, from development to deployment, monitoring, and ongoing maintenance.

  • Ensure AI/ML models are seamlessly integrated into the organization's systems and workflows.

  • Evaluate and implement AI and ML tools, frameworks, and platforms (e.g., TensorFlow, PyTorch, Scikit-learn, etc.) to support advanced analytics capabilities.

  • Analyze data system performance and implement optimization strategies to ensure high scalability and reliability of AI/ML solutions.

  • Optimize AI/ML algorithms for efficiency, accuracy, and performance across large datasets.

  • Collaborate with data engineers, analysts, and business stakeholders to ensure the successful adoption and scaling of AI/ML initiatives.
  • Work closely with cross-functional teams to identify and prioritize AI opportunities that deliver the highest business impact.

  • Educate teams and stakeholders on the practical applications of AI and machine learning within the organization.

  • Implement AI models and data solutions with a strong focus on data privacy, security, and compliance with regulations like GDPR and CCPA.

  • Enforce security protocols to protect sensitive data and ensure responsible AI usage.

  • Stay up to date with the latest advancements in AI/ML technologies, frameworks, and methodologies, driving innovation in data-driven solutions.

  • Identify opportunities to leverage emerging AI trends, such as deep learning, NLP, or computer vision, to address business needs.

  • May need to work outside of normal work hours supporting 24/7 operations (i.e., evenings and weekends).

  • Performs other duties and tasks as assigned.

  • Review invoices and approving them if the work has contractual standards.

  • Address performance issues with the contractor when possible.

  • Escalate issues to other parties as needed.

  • Abide with MTA attendance expectations and requirements by attending regularly and reliably.

  • Provide technical advice to project teams and mentor less experienced staff to foster talent development.

  • Observing the work performed by the contractor.

KNOWLEDGE, SKILLS AND ABILTIES

Technical Skills:
  • Experience working with Enterprise Architecture
  • Experience in the ML/AI domain
  • Adept in Python, Data Science, Data Engineering & MLOPS
  • Adept in cloud architecture and development
  • Adept in cloud operation & management
  • Adept in virtualization and cloud platforms.
  • Adept in cloud services (e.g., analytics).
  • Adept in cloud computing, cloud solutions, cloud automation, cloud services (e.g., analytics).
  • Adept in analyzing storage needs, performance tuning, and capacity planning
  • Adept in Disaster Recovery principles and tools, including complex recovery environments and comprehensive risk assessments.
  • Adept in compute services management
  • Adept in data services management
  • Adept in software development
  • Adept in computer science.
  • Adept in Databricks, PySpark, Python, R, and AWS components such as EventBridge, Lambda, etc.
  • Adept in RESTful API design and implementation
  • Adept in Web framework like Fast API/Tornado/Flask etc.
  • Adept in designing MLOps platforms and architecting big data systems on Google Cloud Platform cloud.
  • Adept in designing post-deployment model management framework e.g. model monitoring tools, workflows for feature drift, error analysis of models
  • Adept in designing CI/CD pipelines (Jenkins) for deployment of Data Engineering and ML jobs workflow.
  • Adept in orchestration frameworks like Airflow, Cloud Composer, DataProc Serverless for Pyspark jobs etc.
  • Adept in DMBoK
  • Data Science knowledge and familiarity with ML libraries such as Pandas, Scikit, TensorFlow, xgboost, time series frameworks like prophet/or equivalent frameworks
  • Knowledge of design patterns and architecture, data science, and machine learning best practices
  • Working knowledge of ML frameworks, such as Vertex, Kubeflow, MLflow, CloudRun etc.
  • Hands on design and coding is required and review code, refactor if necessary, and play a hands-on role in coding critical areas yourself
  • Experience with relational databases like Big Query, cloud environments, and a good understanding of optimizing storage cost/query cost while designing data engineering workflows
  • Good knowledge of Kubernetes, container technologies, docker registries, and applying them in the context of machine learning systems.
  • In-depth understanding of Google Cloud ecosystem for Data Engineering & MLOps - cloud composer, dataproc, serverless, big query, cloud run, vertex, vertex pipelines, GKE.

Behavioral Skills:
  • Advanced in establishing and maintaining effective working relationships with employees at all levels within the organization, and with both internal and external customers.
  • Advanced in interpersonal and verbal and written communication skills, with the ability to effectively collaborate with both technical and non-technical peers.
  • Advanced in communicating effectively, both orally and in writing, to interact with team members, customers, management, and support personnel (technical and non-technical)
  • Adept in identifying and analyzing risks and developing effective mitigation strategies.
  • Adept in critical thinking, problem-solving, and decision-making skills.
  • Adept in active listening, attention to detail, customer service, prioritization, and problem-solving skills.
  • Adept in hands-on experience with related tools.
  • Adept in working independently and strategically.
  • Adept technical knowledge and diverse skillset to understand various technologies, systems, and potential risks.
  • Adept in managing multiple projects simultaneously and prioritizing tasks based on urgency and impact.
  • Adept with working under pressure and meet deadlines individually and collaboratively. Thinks logically, assesses problems, and is results oriented.
  • Adept in identifying complex business and technology risks and associated vulnerabilities.


EDUCATION AND EXPERIENCE

Qualifications:
  • Education: Bachelor's degree and minimum of 10 years of relevant experience. An equivalent combination of education and experience may be considered in lieu of a degree.
  • Certification(s): Requires at least two certifications in the current platform/domain/technical skill. Possible certifications could be, but are not limited to:

Relevant Certifications

TOGAF (The Open Group Architecture Framework)

SAS Certified Data Scientist

Certified Information Management Professional (CIMP)

AWS Certified Machine Learning - Specialty

Certified Data Management Professional (CDMP)

Google Professional Machine Learning Engineer

IBM Certified Data Architect - Big Data

Microsoft Certified: Azure AI Engineer Associate

Oracle Certified Professional, Oracle Database Architect

AWS Certified Solutions Architect

Cloudera Certified Data Professional (CCDP)

Google Professional Cloud Architect

Databricks Certified Data Engineer Associate

Microsoft Certified: Azure Solutions Architect Expert

Oracle Data Management and Modeling

Microsoft Certified: Azure Data Engineer Associate

CIMP Data Modeling

Amazon Web Services (AWS) Certified Big Data - Specialty

Dataversity's Data Modeling Certified Professional (DMCP)

IBM Certified Data Engineer

COMPETENCIES:

Core Competency

Proficiency Level

Competency Definition

Collaborates

Expert

Building partnerships and working collaboratively with others to meet shared objectives

Cultivates Innovation

Advanced

Creating new and better ways for the organization to be successful

Customer Focus

Advanced

Building strong customer relationships and delivering customer-centric solutions

Communicates Effectively

Expert

Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences

Tech Savvy

Expert

Anticipating and adopting innovations in business-building digital

and technology applications

Technical Skills

Expert

Specialized knowledge and expertise on tools, programs, domains, platforms, and products used for specific tasks

Values Diversity

Expert

Recognizing the value that different perspectives and cultures bring to an organization

  • May need to work outside of normal work hours (i.e., evenings and weekends)
  • Travel may be required to other MTA locations or other external sites.

Other Information

Pursuant to the New York State Public Officers Law & the MTA Code of Ethics, all employees who hold a policymaking position must file an Annual Statement of Financial Disclosure (FDS) with the NYS Commission on Ethics and Lobbying in Government (the "Commission").

Equal Employment Opportunity

MTA and its subsidiary and affiliated agencies are Equal Opportunity Employers, including with respect to veteran status and individuals with disabilities.

The MTA encourages qualified applicants from diverse backgrounds, experiences, and abilities, including military service members, to apply.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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