Haparz Pvt Ltd
https://haparz.comAbout
At Haparz, we help businesses turn ideas into powerful digital products. We specialize in building custom mobile applications, websites, software solutions, AR/VR experiences, games, and blockchain applications that are secure, scalable, and designed to deliver real business impact. By combining technical expertise with a client-first approach, we create solutions tailored to each organization's unique goals.
We believe great products are built by great teams. Our experienced designers, developers, and technology specialists work closely with clients at every stage of the development journey—from ideation and strategy to deployment and ongoing support. Whether you're a startup launching your first product or an enterprise scaling your digital presence, we're committed to delivering high-quality solutions that help you innovate, grow, and stay ahead of the competition.
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Jobs at Haparz Pvt Ltd
Amazon Web Services (AWS)Job description: Data Architect – Databricks / AWS
Job Summary
We are looking for an experienced Data Architect to define and drive the target data architecture for the Horizon MVP and its future evolution. The role will be responsible for designing a scalable, secure, governed cloud data platform covering ingestion, storage, processing, analytics, APIs, and downstream data consumption.
The architect will work closely with Data Engineering, Backend, DevOps, QA, and business stakeholders to establish architecture standards and ensure the platform is ready for advanced analytics, AI/ML, vector storage, and future LLM-based capabilities.
- Job Title: Data Architect
- Experience: 8+ Years
- Relevant Architecture Experience: 3+ Years in Data Architecture
- Location: Chennai / Pune
- Work Mode: Hybrid – 3 Days WFO
- Budget: Up to 24 LPA
- Payroll: Haparz
- Notice Period: Immediate Preferred
Key Responsibilities
- Define the target data architecture for the Horizon MVP and establish an architecture roadmap for future scalability.
- Design end-to-end architecture covering data ingestion, storage, processing, serving, reporting, APIs, and downstream applications.
- Establish canonical data models and schemas for travel signals, corridors, sources, evidence, scores, and generated insights.
- Define data normalization strategies for structured, semi-structured, and unstructured data from multiple external sources.
- Design and govern the Databricks platform architecture, including Unity Catalog, data schemas, access controls, and governance standards.
- Establish data-retention, lineage, data-quality, security, privacy, and compliance controls.
- Define secure integration patterns between Databricks, AWS PRODIGY, SharePoint, external APIs, and downstream applications.
- Design scalable data processing for 30-day signal windows, convergence/divergence scoring, corridor ranking, and spike detection.
- Define architecture patterns that support future vector storage, embeddings, LLM integration, and multi-year analytics.
- Design reliable batch and API-driven ingestion frameworks for structured and unstructured data.
- Review technical designs, identify architectural risks, and provide technical direction to engineering teams.
- Guide backend, data engineering, DevOps, and QA teams in implementing architecture standards.
- Ensure architecture decisions align with enterprise security, RBAC, PII handling, privacy, and operational requirements.
- Communicate architecture decisions, trade-offs, and technical recommendations effectively to technical and business stakeholders.
What We’re Looking For
- 8+ years of experience in data engineering, data platforms, or data architecture, with at least 3+ years in a Data Architect capacity.
- Strong hands-on experience designing cloud-based data platforms, lakehouses, or analytical platforms.
- Advanced knowledge of Databricks, Apache Spark/PySpark, Delta Lake, and Unity Catalog.
- Strong understanding of AWS data services, IAM, networking, and secure cloud integration patterns.
- Strong expertise in data modelling, metadata management, data lineage, data quality, retention, and governance.
- Experience architecting batch and API-based ingestion pipelines for structured, semi-structured, and unstructured data.
- Understanding of AI/ML workloads, feature pipelines, vector databases, embeddings, and LLM integration patterns.
- Experience designing APIs and downstream data-serving architectures.
- Strong knowledge of PII protection, RBAC, data privacy, and enterprise security controls.
- Excellent architectural communication and stakeholder-management skills.
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