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Vacancy description

Data Architect in Bangalore, भारत

ALTRAIZE

Bangalore, भारत

Role Overview

The Data Architect (Oil & Gas) will lead end to end data architecture strategy, solution design, and implementation for global Oil & Gas clients. (upstream, midstream, or downstream). The candidate will drive data modernization, enterprise data platforms, and advanced analytics adoption as part of large-scale digital transformation engagements.

Key Responsibilities

Data Architecture & Strategy:
  • Define enterprise grade data architecture blueprints, reference models, and design patterns for Oil & Gas clients.
  • Architect data platforms leveraging cloud ecosystems (Azure, AWS, GCP) with strong focus on scalability, security, data quality, and governance.
  • Design logical and physical data models, data flows, and integration architectures aligned to Oil & Gas business processes.
  • Establish architectural standards for master data, metadata, lineage, ontologies, and taxonomy frameworks.
  • Incorporate emerging technologies such as AI/ML, knowledge graphs, IoT/SCADA data pipelines, predictive analytics, and industry frameworks like OSDU.

  Solution Delivery & Technical Leadership:

  • Lead cross functional delivery teams across data engineering, analytics, integration, and platform modernization.
  • Oversee end to end data platform implementations, ensuring architectural integrity, performance, and reliability.
  • Conduct technical design reviews, provide hands on guidance, and ensure adherence to best practices and enterprise architecture guardrails.
  • Partner with cloud, application, and domain teams to ensure seamless integration across enterprise systems.
  • Drive high quality deliverables by ensuring robust testing, validation, and deployment practices.

Oil & Gas Domain Enablement:

  • Apply data architecture principles to Oil & Gas business domains including:
  • Production operations
  • Asset management
  • Drilling and subsurface data
  • Pipeline operations
  • Refining and petrochemicals
  • Architect data ingestion and harmonization of time-series, geospatial, subsurface, and IoT data.
  • Advise clients on adopting Oil & Gas industry data standards, with a strong understanding of OSDU Data Platform and domain data models.

Stakeholder & Client Management:

  • Act as a senior advisor to client architecture leaders, supporting C level stakeholders with data-driven strategies.
  • Communicate architectural concepts to technical and non-technical stakeholders with clarity.
  • Manage vendor engagements and technology partners to ensure alignment to standards and client objectives.
  • Contribute to proposals, pursuit teams, and thought leadership for Oil & Gas data transformation initiatives.

Optimization & Continuous Improvement:

  • Conduct architecture maturity assessments and define modernization roadmaps.
  • Identify opportunities for performance optimization, cost reduction, and data lifecycle efficiency.
  • Create reusable assets, accelerators, and frameworks to improve project delivery velocity across Energy Limited teams.

Required Qualifications:

  • 7+ years of overall experience in data architecture, data engineering, and enterprise data management.
  • 3+ years of hands on experience in Oil & Gas industry projects (upstream, midstream or downstream).
  • Proven experience designing and delivering large-scale cloud data platforms (Azure/AWS/GCP).

Strong expertise in:

  • Data modeling (conceptual, logical, physical)
  • Data integration & ETL/ELT pipelines
  • Data governance and quality frameworks
  • Time-series, IoT, and real time data platforms
  • Experience with OSDU, SCADA/IoT data, geospatial datasets, and subsurface data structures preferred.
  • Strong leadership, stakeholder management, and client facing communication skills.
  • Experience leading distributed global teams and working in multi vendor environments.

Preferred Skills:

  • Strong Experience with Oil & Gas analytics platforms, digital oilfield solutions, and asset performance systems.
  • Certification in Cloud platforms (Azure, AWS, or GCP).
  • Experience with AI/ML use cases applied to O\&G operations and asset management.
  • Understanding of DevOps/DataOps, containerization, and microservices architecture.
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