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Data Architect

TalentOla


Job Location:

New York City, NY - USA

Monthly Salary: Not provided by the employer
Posted: 1 June 2026 (30+ days ago)
Application Deadline: 29 August 2026
Vacancies: 1 Vacancy
The job posting is outdated and position may be filled

Job Summary

Job Title: Data Architect

Role Summary

We are seeking a highly skilled and forward-thinking Data Architect who combines strong strategic vision with hands-on technical expertise. This role will be responsible for defining the organizations data strategy designing scalable data architectures and actively contributing to implementation across all data-driven initiatives.

The ideal candidate will bridge business and technology ensuring data solutions align with organizational goals while being robust secure and future-ready.

Key Responsibilities

1. Data Strategy & Governance

  • Define and drive the enterprise data strategy aligned with business objectives.
  • Establish data governance frameworks policies standards and best practices.
  • Lead data architecture roadmaps covering data platforms integration storage and analytics.
  • Partner with business stakeholders to identify data-driven opportunities and ensure value realization.
  • Ensure compliance with data privacy security and regulatory requirements.

2. Architecture Design

  • Design and own end-to-end data architecture (batch real-time streaming).
  • Develop scalable solutions across:
    • Data Warehousing / Data Lakes / Lakehouses
    • Cloud platforms (Azure AWS GCP)
    • Big Data ecosystems
  • Define data models (conceptual logical physical) for enterprise systems.
  • Establish standards for data integration APIs and metadata management.

3. Hands-on Technical Leadership

  • Actively participate in solution design and development (not just oversight).
  • Build and review:
    • Data pipelines (ETL/ELT)
    • Data ingestion frameworks
    • Data transformation processes
  • Optimize performance scalability and reliability of data systems.
  • Conduct architecture reviews code reviews and design validations.

4. Platform & Technology Enablement

  • Evaluate and recommend tools technologies and platforms.
  • Drive adoption of modern practices such as:
    • DataOps
    • MLOps (where applicable)
    • Data Mesh / Data Fabric paradigms
  • Enable self-service analytics and business intelligence capabilities.

5. Stakeholder Management

  • Collaborate with:
    • Business leaders
    • Engineering teams
    • Product managers
  • Translate business requirements into technical solutions.
  • Mentor and guide data engineers analysts and other architects.