Technical Architect

About the Company

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.