Data Platform Engineer

Robustrade FZCO; Pune District; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

Robustrade FZCO is seeking a data engineer to build and optimize scalable ETL/ELT pipelines for structured and unstructured data in a dynamic environment. You will design batch and real-time streaming pipelines with Spark, Kafka, and Flink, and develop data models for analytics and product use cases.

The role requires hands-on coding in Python, Java, Go, or Ruby, plus experience with Airflow, DBT, Spark, and cloud platforms such as AWS, GCP, or Azure.

Qualifications

• 3–8 years of experience in data platform or data engineering roles.
• Strong proficiency in SQL and experience with relational and NoSQL databases.
• Hands-on experience with Airflow, DBT, Spark, or Flink.
• Experience with streaming or batch data processing systems.
• Proficiency in at least one programming language (Python, Go, or Java).
• Familiarity with cloud platforms (AWS, GCP, or Azure).

Responsibilities

• Build and maintain scalable ETL/ELT data pipelines for structured and unstructured data.
• Design and optimise batch and real-time streaming pipelines using Spark, Kafka, Flink, etc.
• Develop and maintain data models for analytics and product use cases.
• Write clean, scalable, production-grade code using Python, Java, Go, or Ruby.
• Build internal data services, integrations, automation, and developer tools.
• Ensure data quality, integrity, availability, reliability, and performance.
• Implement monitoring, logging, alerting, and automated testing for data pipelines.
• Troubleshoot pipeline failures and optimize performance, scalability, and cost.
• Collaborate with Product, Analytics, and Engineering teams on data requirements.
• Participate in system design and architecture discussions.
• Follow best practices around data governance, security, and compliance.

Skills

SQL proficiency

Data pipeline design

Collaborative teamwork

Tools

Airflow

DBT

Spark

Flink

Python

Go

Java

Kafka

AWS

GCP

Azure

NoSQL databases

Job description

Responsibilities:

• Build and maintain scalable ETL/ELT data pipelines for structured and unstructured data.
• Design and optimise batch and real-time streaming pipelines using Spark, Kafka, Flink, etc.
• Develop and maintain data models for analytics and product use cases.
• Write clean, scalable, production-grade code using Python, Java, Go, or Ruby.
• Build internal data services, integrations, automation, and developer tools.
• Ensure data quality, integrity, availability, reliability, and performance.
• Implement monitoring, logging, alerting, and automated testing for data pipelines.
• Troubleshoot pipeline failures and optimize performance, scalability, and cost.
• Collaborate with Product, Analytics, and Engineering teams on data requirements.
• Participate in system design and architecture discussions.
• Follow best practices around data governance, security, and compliance.

Requirements:

• 3-8 years of experience in data platform or data engineering roles.
• Strong proficiency in SQL and experience with relational and NoSQL databases.
• Hands-on experience with Airflow, DBT, Spark, or Flink.
• Experience with streaming or batch data processing systems.
• Proficiency in at least one programming language (Python, Go, or Java).
• Familiarity with cloud platforms (AWS, GCP, or Azure).

Nice to Have:

• Experience with real-time streaming (Kafka, Kinesis, Pub/Sub).
• Exposure to data warehouses (Snowflake, BigQuery, Redshift).
• Experience operating data platforms in high-scale or fintech domains.
• Understanding of data security, privacy, and compliance.