Data Solution Architect

Neurealm; Chennai District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Neurealm seeks an experienced Data Solution Architect to design and implement large-scale data platforms. You will lead architecture for Databricks, Azure, and GCP, delivering scalable, cost-aware pipelines and analytics solutions that translate business needs into data models and workflows.

Responsibilities include defining governance, building reusable components, and presenting animated data flows to technical and business audiences. Strong communication and cloud expertise are essential.

Qualifications

• 10–12+ years experience in data engineering, analytics, or architecture roles.
• 2–4+ years hands-on Databricks experience (mandatory).
• Deep experience with Azure and GCP cloud ecosystems.
• Strong expertise in Spark, PySpark, SQL, Python.
• Proficiency in data modeling, ETL frameworks, and distributed data systems.
• Experience with streaming technologies (Kafka, Event Hub, Pub/Sub).
• Ability to design and present animated architecture and data flows.
• Strong communication and stakeholder management skills.

Responsibilities

• Design end-to-end data lakehouse, data warehouse, and analytics architectures using Databricks, Azure, and GCP.
• Build scalable and cost-optimized architectures for ingestion, transformation, streaming, and ML workloads.
• Define and enforce architecture standards, patterns, and governance models.
• Translate business requirements into logical and physical data models.

Skills

Databricks

Azure

GCP

Spark

PySpark

SQL

Python

Data modelling

ETL frameworks

Kafka

Tools

Databricks

Azure

Unity Catalog

Delta Lake

MLflow

DLT

Dataflow

ADF

Job description

We are looking for an experienced Data Solution Architect to design, architect, and implement large-scale data platforms and analytics solutions. The ideal candidate will have strong hands-on experience in Databricks, Azure, and Google Cloud Platform (GCP), along with the ability to create animated/visual data stories for technical and business audiences.

Candidate will play a key role in defining data strategy, optimizing data pipelines, ensuring platform scalability, and developing reusable frameworks.

Required Skills & Experience

• 10–12+ years overall in data engineering, analytics, or architecture roles.
• 2–4+ years strong hands-on experience in Databricks (mandatory).
• Deep experience with Azure and GCP cloud ecosystems.
• Strong expertise in Spark, PySpark, SQL, Python.
• Proficiency in data modeling, ETL frameworks, and distributed data systems.
• Experience with streaming technologies (Kafka, Event Hub, Pub/Sub).
• Ability to design and present animated architecture and data flows.
• Strong communication and stakeholder management skills.

Key Responsibilities

• Design end-to-end data lakehouse, data warehouse, and analytics architectures using Databricks, Azure, and GCP.
• Build scalable and cost-optimized architectures for ingestion, transformation, streaming, and ML workloads.
• Define and enforce architecture standards, patterns, and governance models.
• Translate business requirements into logical and physical data models.

Databricks Expertise

• Architect and optimize Databricks Lakehouse solutions using Delta Lake, Unity Catalog, Databricks SQL, MLflow, Auto Loader, and DLT.
• Implement advanced transformations using PySpark, Spark SQL, and notebooks.
• Design job orchestration using Databricks Workflows or other orchestration tools.
• Architecture of secure and scalable data systems on Azure.

GCP

• Hands-on experience designing lakehouse/analytics solutions on GCP.
• Lead development of batch and real-time data pipelines using Spark, ADF, Dataflow, or Databricks Workflows.
• Implement ETL/ELT frameworks, CI/CD, and reusable components.

Security & Governance

• Implement data governance frameworks including Unity Catalog, encryption, and compliance.
• Ensure best practices for cost optimization, monitoring, and performance tuning.