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Shuru Technologies Private Limited

Lead Data Engineer

Shuru Technologies Private Limited

IT Services and IT Consulting · 51-200 employees

Yesterday
Remote data-engineer Principal (10+ yrs) Full-time
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About the role

Design, build, and manage scalable multi-cloud data platforms while developing real-time and batch data pipelines. Drive technical architecture, mentor engineering staff, and ensure high standards for data reliability and security.

What they look for

Data Engineering Kafka Spark GCP BigQuery Airflow Terraform Kubernetes Apache Iceberg Delta Lake Data Modeling Distributed Systems Data Warehouse Architecture Technical Leadership Mentoring Data Governance

Requirements

Requires 8+ years of experience in data engineering with at least 3 years operating large-scale production platforms. Strong hands-on expertise in Kafka, Spark, GCP, BigQuery, and infrastructure automation tools like Terraform and Kubernetes is essential.

Benefits

Challenging large-scale engineering and data projects Modern technology stack Collaboration with industry leaders Ownership of architecture and technical decisions Remote-first work environment Career growth and leadership opportunities

Full description

This is a remote position.

Shuru is an AI-native technology and engineering company that partners with businesses to build and scale high-impact digital products, platforms, and AI-driven solutions. We work with fast-growing organizations across industries, helping them solve complex technology challenges through strong engineering, product, data, and AI capabilities.

We are looking for a Senior Data Engineer to join Shuru and help design and build scalable, reliable, and high-performance data platforms for complex business environments.

Key Responsibilities

  • Design, build, and manage scalable multi-cloud data platforms.
  • Develop and optimize real-time and batch data pipelines using Kafka and Spark.
  • Build Lakehouse architectures using Apache Iceberg or Delta Lake.
  • Optimize BigQuery, data models, queries, and warehouse performance.
  • Design reliable and scalable distributed data processing systems.
  • Automate infrastructure and deployments using Terraform and Kubernetes.
  • Ensure high standards of data reliability, security, governance, and compliance.
  • Drive technical architecture and design reviews.
  • Mentor engineers and contribute to engineering best practices.

Requirements

  • 8+ years of experience in Data Engineering, Data Platforms, or Distributed Systems.
  • 3+ years of experience operating large-scale data platforms in production.
  • Strong hands-on experience with Kafka, Spark, GCP, BigQuery, and Airflow.
  • Experience with Terraform and Kubernetes.
  • Hands-on knowledge of Lakehouse technologies such as Iceberg or Delta Lake.
  • Strong understanding of data modeling, distributed systems, and data warehouse architecture.
  • Experience leading technical initiatives and mentoring engineers.

Nice to Have

  • Experience with Debezium, Redpanda, and dbt.
  • Experience with Prometheus and Grafana for monitoring and observability.
  • Exposure to fintech, financial services, or regulated environments.
  • Understanding of data governance, security, and compliance requirements.

Benefits

  • Work on challenging, large-scale engineering and data problems.
  • Build modern platforms using cutting-edge cloud and data technologies.
  • Work closely with experienced engineering, product, and technology leaders.
  • Opportunity to take ownership of architecture and key technical decisions.
  • Remote-first and collaborative work environment.
  • Strong opportunities for learning, leadership, and career growth.

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