Lead Data Engineer

ShuruTech; United States; Remote; USD 140,000 - 180,000; Full time

Job summary

Shuru Technologies Private Limited, an AI-native tech company, seeks a Senior Data Engineer to design scalable data platforms across multi-cloud environments. You will build real-time and batch pipelines with Kafka and Spark, implement Lakehouse architectures, optimize BigQuery and data warehouses, and drive architecture reviews.

You will mentor engineers and automate deployments with Terraform and Kubernetes, ensuring data reliability, security, and governance while collaborating with product

Qualifications

• 8+ years in Data Engineering, Data Platforms, or Distributed Systems.
• 3+ years operating large-scale data platforms in production.
• Strong hands-on with Kafka, Spark, GCP, BigQuery, Airflow.

Responsibilities

• Design, build, and manage scalable multi-cloud data platforms.
• Develop and optimize real-time and batch data pipelines with Kafka and Spark.
• Build Lakehouse architectures using Iceberg or Delta Lake.
• Optimize BigQuery, data models, queries, and warehouse performance.
• Automate infrastructure with Terraform and Kubernetes.
• Ensure data reliability, security, governance, and compliance.
• Drive architecture reviews and mentor engineers.

Skills

Kafka

Spark

GCP

BigQuery

Airflow

Terraform

Kubernetes

Iceberg/Delta Lake

Data modeling

Distributed systems

Mentoring

Tools

Terraform

Kubernetes

Debezium

Redpanda

dbt

Prometheus

Grafana

Job description

Shuru Technologies Private Limited | Full time

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.
• 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.