Staff Software Engineer (Data Platform)

Arcana; Bengaluru; Hybrid; INR 4,500,000 - 7,500,000; Full time

Job summary

Arcana in Bengaluru seeks a Staff Software Engineer to design and scale distributed data platforms, focusing on batch and real-time processing across ingestion, transformation, and serving layers.

You will lead data platform initiatives, mentor engineers, and optimize queries on ClickHouse and other columnar stores while leveraging AWS/GCP to deliver production-grade solutions.

Qualifications

• Bachelor's degree in CS, IT or a related field.
• 8+ years in data engineering or distributed systems.
• Proven track record building scalable data platforms and large-scale data systems.
• Strong ETL, data integration, and workflow orchestration experience.

Responsibilities

• Design and build scalable data platform components for batch and real-time data processing.
• Architect, develop, and operationalize large-scale data systems across ingestion, transformation, and serving layers.
• Build and manage robust data pipelines ensuring high reliability, scalability, and cost efficiency.
• Develop reusable frameworks and tooling to accelerate productivity for data engineers and data scientists.
• Leverage Python, Airflow, SQL, and cloud platforms to build production-grade data solutions.
• Optimize query performance and data models using columnar OLAP systems (ClickHouse, Doris, StarRocks).
• Implement streaming and near real-time data processing systems.
• Translate complex business requirements into scalable data platform solutions.
• Work with cross-functional teams and provide technical leadership and mentorship.
• Drive architectural decisions by evaluating tradeoffs and selecting the right tools.

Skills

Python

SQL

Airflow

Temporal

Cloud AWS

Cloud GCP

Spark

ClickHouse

PostgreSQL

Cassandra

Elasticsearch

Kafka

Docker

Kubernetes

Linux

Education

Bachelor's Degree in Computer Science or related

Tools

Airflow

Temporal

ClickHouse

PostgreSQL

Cassandra

Elasticsearch

Kafka

Docker

Kubernetes

Spark

Job description

Staff Software Engineer (Data Platform) Join our dynamic team at the forefront of cutting-edge technology as we seek a seasoned Staff Data Engineer. Embark on a journey where your deep-rooted expertise in distributed systems, data architectures, and large-scale processing becomes the cornerstone of building high-performance data platforms. This pivotal role demands proficiency in designing and scaling compute and I/O-intensive data systems, ensuring reliability, efficiency, and cost optimization across the data lifecycle.

Responsibilities

• Design and build scalable data platform components for batch and real-time data processing.
• Architect, develop, and operationalize large-scale data systems across ingestion, transformation, and serving layers.
• Build and manage robust data pipelines ensuring high reliability, scalability, and cost efficiency.
• Develop reusable frameworks and tooling to accelerate productivity for data engineers and data scientists.
• Leverage expertise in Python, Airflow, SQL, and cloud platforms to build production-grade data solutions.
• Optimize query performance and data models using strong understanding of columnar OLAP systems such as ClickHouse, Doris, and StarRocks.
• Implement streaming and near real-time data processing systems.
• Translate complex business requirements into scalable and efficient data platform solutions.
• Work collaboratively with cross-functional teams and provide technical leadership and mentorship.
• Drive architectural decisions by evaluating tradeoffs and selecting the right tools for the problem.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, or a similar discipline.
• 8+ years of professional experience in data engineering, backend systems, or distributed systems.
• Proven experience building scalable data platforms and large-scale data systems.
• Strong experience with ETL pipelines, data integration, and workflow orchestration systems such as Airflow or Temporal.
• Hands-on experience in Python and SQL with strong understanding of data warehouse concepts.
• Experience working with distributed OLTP/OLAP databases such as ClickHouse, PostgreSQL, Cassandra, or Elasticsearch.
• Knowledge of messaging and streaming systems such as Kafka.
• Experience with cloud platforms (AWS/GCP) and big data tools such as Spark.
• Strong understanding of columnar storage systems and query optimization techniques.
• Solid understanding of distributed systems fundamentals and associated tradeoffs.
• Experience working with containers and orchestration tools such as Docker and Kubernetes.
• Strong Linux fundamentals and system-level debugging skills.
• Familiarity with modern data architectures such as Lakehouse (Iceberg, Hudi, Delta) is a plus.