JD - Data Guard Architect

Role Type: Individual Contributor (IC) Product Strategy & Architecture
Experience: 8+ Years
Role Overview
We are looking for an experienced DataGuard Architect to drive product vision, data governance, and
technical architecture for an existing data product. This individual will combine a product management
mindset with deep expertise in data governance and data engineering to assess existing capabilities,
identify gaps, and dene enhancements that deliver measurable business value. The role requires solid
knowledge of data quality, metadata architecture, data ows, and data pipelines, along with technical
expertise in Python, FastAPI, Databricks, and Snowake. SAP experience is an added advantage.
Key Responsibilities
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Product Vision & Strategy: Dene and evolve the product vision, identify opportunities to
enhance existing capabilities, and recommend changes that deliver measurable business value.
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Product Roadmap & Prioritization: Assess existing product capabilities, identify functional and
architectural gaps, and prioritize enhancements based on business value, user needs, technical
feasibility, and strategic objectives.
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Data Governance: Dene and strengthen governance frameworks covering data quality,
metadata management, data lineage, data ownership, data standards, and governance controls.
Data Quality Management: Establish data quality rules, validation mechanisms, monitoring
processes, and controls to improve data accuracy, completeness, consistency, and reliability.
Data Architecture: Design and improve metadata architecture, data ow architecture, and end-
to-end data pipelines to ensure scalability, reliability, traceability, and governance.
Technical Architecture: Drive architectural decisions for product enhancements, ensuring
alignment with enterprise data architecture, technology standards, security, and scalability
requirements.
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Solution Design & Integration: Collaborate with engineering teams to translate product




requirements into scalable solutions using Python, FastAPI, Databricks, and Snowake.
Product Innovation: Identify opportunities to automate data governance, improve metadata
visibility, strengthen data controls, and enhance product usability and operational eiciency.
Stakeholder Management: Work with business stakeholders, product teams, and engineering
teams to understand challenges, validate proposed solutions, and align priorities.
Continuous Improvement: Evaluate existing product performance and architecture to identify
opportunities for improved functionality, scalability, maintainability, and business impact.
Required Skills
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Data Governance: Strong expertise in enterprise data governance, data quality management,
metadata management, data lineage, and governance frameworks.
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Product Management Mindset: Experience dening product vision, identifying improvement
opportunities, prioritizing features, and driving value-based product enhancements.
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Data Architecture: Strong understanding of metadata architecture, data ow architecture, data
models, and end-to-end data pipeline design.
Data Engineering: Experience with data processing, pipeline development, data integration, and
data quality implementation.
Python & FastAPI: Strong Python knowledge and familiarity with FastAPI for developing or
integrating data services and APIs.
Databricks & Snowake: Hands-on experience or strong technical understanding of modern
data platforms, including data processing, storage, integration, and governance capabilities.
Architecture & Problem Solving: Ability to assess existing systems, identify technical and
functional gaps,



and recommend scalable solutions.
Stakeholder Management: Strong analytical, communication, and collaboration skills, with the
ability to translate business requirements into technical solutions.
Individual Contribution: Ability to independently drive product and architecture decisions while
collaborating with cross-functional teams.
Preferred Skills
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Data Product Development: Experience building, managing, or enhancing enterprise data
products.
Product Strategy: Exposure to product roadmap denition, feature prioritization, technical
product ownership, or product lifecycle management.
SAP Knowledge: Familiarity with SAP systems, enterprise data models, and SAP data
integration.
Enterprise Integration: Experience integrating data governance capabilities with enterprise
applications and modern data platforms.
Cloud Data Architecture: Familiarity with cloud-based data ecosystems and modern data
engineering practices.
Minimum Qualications
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Education: Bachelors or Masters degree in computer science, Engineering, Information
Technology, or a related eld.
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Experience: 8+ years of relevant experience in Data Governance, Data Architecture, Data
Engineering, or Data Product Development, with demonstrated expertise in data governance,
technical architecture, and product enhancement initiatives.
Ideal Candidate Prole
The ideal candidate is a senior individual contributor who combines strong data governance expertise,
data engineering knowledge, and a product-oriented mindset. They should be capable of evaluating an
existing data product, identifying gaps and opportunities, dening a clear product vision, and translating
business needs into scalable technical enhancements. The candidate should be comfortable driving
architecture decisions and collaborating with engineering teams to deliver measurable product value.
Experience with SAP and enterprise data environments is an added advantage.
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📌 Data Guard Architect (Hyderabad)
🏢 Sigmoid
📍 Hyderabad