Principal Data Architect

EvoluteIQ; Bengaluru; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

EvoluteIQ is seeking an experienced Technical Architect (Data) to lead the architecture of a low-code data pipeline and hyperautomation platform. The ideal candidate should have 15+ years of software engineering experience, including 4+ in data architecture. Responsibilities include designing scalable systems for data processing, leading technology choices, and mentoring teams. Strong skills in Python, distributed systems, and data storage technologies are essential. This role presents an exciting opportunity for the right candidate to make a significant impact in data architecture.

Qualifications

• 15+ years in software engineering with 4+ years in data architecture roles.
• Hands-on experience with distributed systems and data processing frameworks.
• Experience with cloud data warehouses like Snowflake or BigQuery.

Responsibilities

• Define and evolve data platform architecture for real-time and batch data processing.
• Design scalable, multi-tenant, cloud-native systems supporting data pipelines.
• Lead architecture reviews and mentor engineering teams.

Skills

Distributed data systems

Cloud-native design

Python expertise

Data storage systems

Kubernetes

ETL builder platforms

Tools

Spark

Kafka

Docker

Terraform

FastAPI

Job description

We are looking for an experienced Technical Architect (Data) to lead the architecture and scalability of our low‑code data pipeline and hyperautomation platform. The ideal candidate has deep expertise in distributed data systems, cloud‑native design, and hands‑on experience building and deploying production‑grade data products at scale.

About the Role

What You’ll Do at EvoluteIQ

• Define and evolve data platform architecture for real‑time and batch data processing.
• Design scalable, multi‑tenant, cloud‑native systems supporting data pipelines and orchestration.
• Guide technology choices across storage, compute, APIs, and orchestration frameworks.
• Ensure production‑grade performance, observability, and resilience.
• Partner with product and engineering teams to translate business requirements into scalable solutions.
• Lead architecture reviews, enforce coding and data quality standards, and mentor engineering teams.

Responsibilities

• 15+ years in software engineering with 4+ years in data architecture roles.
• Hands‑on experience with distributed systems and data processing frameworks (Spark, Flink, Kafka, Airflow, Dagster).
• Strong Python expertise with libraries such as Pandas, PySpark, NumPy, Dask, FastAPI, and SQLAlchemy.
• Experience with Java/Scala/Python, REST/gRPC APIs, microservices, and event‑driven architectures.
• Proficiency with data storage systems (PostgreSQL, MongoDB, Cassandra) and cloud data warehouses (Snowflake, BigQuery, Redshift).
• Familiarity with Kubernetes, Docker, Terraform, and CI/CD pipelines for data workloads.

Qualifications

• Experience with low‑code/no‑code or ETL builder platforms.
• Knowledge of AI/ML data pipelines, model serving, and feature stores.
• Familiarity with data governance, encryption, and compliance (GDPR, SOC2).
• Proven success in taking products from architecture design to production deployment.

Required Skills

• Reliable, high‑performance data systems in production.
• Scalable, modular, and secure architecture.
• Improved throughput, latency, and developer velocity.
• Strong architectural discipline and positive mentoring impact.

Preferred Skills

• Experience with low‑code/no‑code or ETL builder platforms.
• Knowledge of AI/ML data pipelines, model serving, and feature stores.
• Familiarity with data governance, encryption, and compliance (GDPR, SOC2).
• Proven success in taking products from architecture design to production deployment.