Lead Data Architect

Intelli Search; Mumbai; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Intelli Search is seeking a hands-on Lead Data Architect to design and build a next-generation data platform. This is an Individual Contributor role, with responsibilities spanning architecture, coding and production troubleshooting, plus direct client collaboration.

You will architect end-to-end data solutions across Data Lake, Warehouse and Lakehouse, integrating client data with internal datasets, and leading large-scale batch, CDC and real-time pipelines while mentoring peers.

Qualifications

• Strong SQL expertise with hands-on PostgreSQL experience.

Responsibilities

• Design end-to-end data solutions across Data Lake, Warehouse and Lakehouse.
• Integrate client data with internal data into unified datasets.
• Build batch, incremental, CDC and real-time pipelines at large scale.
• Guide data engineers through code reviews and design reviews.
• Optimise very large databases for performance, scalability and cost.

Skills

SQL

PostgreSQL

Python

PySpark

Data modelling

Lakehouse

Cloud

CI/CD

Production systems

Data security

Governance tools

Tools

Azure Databricks

Delta Lake

Microsoft Fabric

Kafka

Event Hubs

Confluent

Microsoft Purview

Job description

We're hiring for a leading financial technology firm. They need a hands‑on Lead Data Architect to design and build a next‑generation data platform from the ground up. This is mainly an Individual Contributor (IC) role. You'll design the architecture, write the code and troubleshoot in production. You'll also work directly with clients and guide the Data Engineering team on design, standards and best practices.

Design and build end-to-end data solutions across Data Lake, Warehouse and Lakehouse platforms. Integrate client data with internal data into reliable, unified datasets. Build batch, incremental, CDC and real‑time pipelines at large scale. Work with clients to understand requirements and translate them into architecture. Guide and review the work of data engineers through code reviews, design reviews and mentoring. Optimise very large databases for performance, scalability and cost.

Strong SQL, with hands‑on PostgreSQL experience. Experience across multiple databases (relational, columnar and/or NoSQL). Data integration from multiple databases and sources (APIs, files, streams, client systems). Has managed and optimised very large databases (TB-scale, high-volume). Python and distributed processing (e.g. PySpark). Data modelling and Data Lake / Warehouse / Lakehouse architecture. Cloud, CI/CD and production data platform experience. Strong communication skills and comfort working with clients.

• Preferred: Financial domain experience: capital markets, fund accounting, asset management, banking or trading.
• Preferred: Exposure to financial datasets: market data, reference data, securities, ETFs, options, indices, portfolio or transaction data.
• Preferred: Azure Databricks / Delta Lake, Microsoft Fabric.
• Preferred: Kafka / Confluent / Event Hubs and event‑driven architecture.
• Preferred: Microsoft Purview or similar governance and catalogue tools.
• Preferred: Data governance, lineage, data quality and observability frameworks.
• Preferred: LLM/AI use in data extraction, enrichment or data‑quality workflows.
• Preferred: Data security and compliance: masking, encryption, access controls, audit.
• Preferred: Certifications such as Databricks, Azure, AWS or DAMA CDMP.