Data Architect

Nuaav; Dadri; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Nuaav is seeking a Technical Solution Architect with 14+ years of engineering experience to own the architectural integrity of a data lakehouse program. The role spans ingestion, storage, semantic layering, REST API exposure, and evolving AI-powered query capabilities.

Responsibilities include end-to-end architecture, implementation oversight for security and performance, and architectural decisions on build-vs-buy and tooling.

Qualifications

• 14+ years of hands-on engineering experience, with 3+ years in a solution / data architect capacity.
• Strong cloud experience and data platform architecture.
• Experience with data lakehouse, semantic layers and AI-enabled query capabilities.

Responsibilities

• End-to-end solution architecture across ingestion, storage, semantic modelling, API exposure, governance and observability.
• Implementation oversight to ensure architecture quality, security, performance and cost.
• Technical decision-making on build-vs-buy, tooling and pattern choices, with clear written rationale.
• Architectural point of contact for client stakeholders, engineering managers, tech leads and data analytics consumers.

Skills

Python

Data modelling

Architectural leadership

REST API design

Tools

AWS

Kafka

Kinesis

Databricks

Snowflake

Job description

We are seeking a Technical Solution Architect with 14+ years of experience to own the end-to-end architectural integrity of this program, from component design, through implementation oversight and deployment, to operationalization. The project centers on a data lakehouse platform that ingests data from heterogeneous sources, organizes it through semantic layers, exposes it via REST APIs, and is being enhanced with AI-powered natural language query capabilities and entity resolution.

Responsibilities

• Key Responsibilities
• End-to-end solution architecture across ingestion, storage, semantic modelling, API exposure, governance and observability.
• Implementation oversight: to ensure it matches the architecture, design quality, security, performance and cost.
• Technical decision-making on build-vs-buy, tooling and pattern choices, with clear written rationale.
• Being the architectural point of contact for client stakeholders, engineering managers, tech leads and data science / analytics consumers.

Qualifications

• Required Qualifications
• 14+ years of hands-on engineering experience, with 3+ years in a solution / data architect capacity.
• Strong AWS experience: comfortable designing on S3, Lambda, API Gateway, IAM and typical data services.
• Deep experience with at least one modern data platform paradigm: data lake, lakehouse, data warehouse, data mesh or data fabric on platforms such as Snowflake, Databricks, Redshift, BigQuery, Synapse, or equivalent.
• Solid grounding in semantic / layered data modelling (raw → business → consumption) and in the trade-offs between virtualization, materialization and copy-based pipelines.
• Strong Python for data pipelines and backend services; comfortable reviewing and writing production-grade code.
• Experience designing and operating REST APIs at scale: versioning, auth, rate limits, pagination, observability, contract discipline.
• Working knowledge of API security and governance patterns: JWT/OAuth, tenant isolation, RBAC / ABAC, field-level access control, audit logging.
• Hands-on experience with real-time event streaming using Kafka, Kinesis, Pulsar or equivalent: producers/consumers, partitioning, ordering and delivery guarantees, schema evolution, back-pressure.

Required Skills

• Production experience with in-memory caching (Redis, Memcached or equivalent) for low-latency reads: cache keys, TTLs, invalidation, hot-key mitigation, and consistency trade-offs.
• Working experience with data lineage, cataloguing and governance tooling (e.g. DataHub, OpenMetadata, Collibra, Alation, Unity Catalog, AWS Glue Data Catalog, or equivalent).
• LLM / RAG patterns applied to structured data: prompt design, grounding against catalogues and dictionaries, evaluation.
• Clear written and verbal communication; able to explain trade-offs to engineers, to engineering managers, and to non-technical stakeholders.

Preferred Skills

• Preferred Qualifications
• Open table formats in production: Apache Iceberg, Delta Lake or Apache Hudi.
• Query / acceleration engines such as Dremio, Trino, Presto, Starburst or Athena.
• Entity resolution / record linkage, either hand-rolled or via tools such as Zingg, Senzing or AWS Entity Resolution.
• Multi-tenant SaaS data platform experience, especially around purpose-of-use controls and regulated workloads.
• Consulting or client-facing delivery experience.
• Soft Skills
• Strong analytical and problem-solving skills.
• High attention to detail.
• Ownership mindset and proactive attitude.
• Ability to work collaboratively in cross-functional environments.