Data Platform Engineer

Salt; Pune District; On-site; INR 1,200,000 - 2,300,000; Full time

Job summary

Salt seeks a Data Platform Engineer in Pune to build and scale reliable data infrastructure and pipelines that empower analytics and product teams. You will design batch and streaming workflows, ensure data quality, and enable fast, secure access to data across the organization.

You will work with technologies like Kafka, Spark, Flink, Airflow, and DBT, and write production-grade code in Python or Java. You will collaborate with product, analytics, and engineering teams to deliver SLAs and

Qualifications

• 4–6 years in data platform or data engineering roles.
• Strong SQL proficiency with relational and NoSQL databases.
• Hands-on experience with Airflow, DBT, Spark, or Flink.
• Experience with streaming or batch data processing systems.
• Proficiency in Python, Go, or Java.
• Familiarity with cloud platforms AWS, GCP, or Azure.

Responsibilities

• Build and maintain ETL/ELT pipelines for structured and unstructured data.
• Design, develop, and optimize batch and streaming pipelines using Kafka, Spark, or Flink.
• Ensure data integrity, availability, and performance across data systems.
• Design and optimize data models for analytics and product use cases.
• Write clean, production-grade code (Python, Java, Go, or Ruby) to support: Data workflows, Internal data services, Integrations and automation.
• Build internal tooling to improve data reliability and developer productivity.
• Partner with product, analytics, and engineering teams to define data needs and infrastructure requirements.
• Contribute to cross-functional system design discussions and architectural reviews.
• Ensure delivery of reliable infrastructure and data solutions that meet SLAs.

Skills

SQL proficiency

Python/Java experience

Data modeling

Cloud familiarity

Tools

Airflow

DBT

Spark

Flink

Kafka

Job description

We are seeking a skilled Data Platform Engineer to build and scale reliable data infrastructure and pipelines. You will enable analytics, product, and business teams by ensuring high-quality, performant, and accessible data across the organization.

Responsibilities

• Build and maintain ETL/ELT pipelines for structured and unstructured data.
• Design, develop, and optimize batch and streaming pipelines using tools such as Kafka, Spark, or Flink.
• Ensure data integrity, availability, and performance across data systems.
• Design and optimize data models for analytics and product use cases.
• Write clean, maintainable, production-grade code (preferably Python, Java, Go, or Ruby) to support:
• Data workflows
• Internal data services
• Integrations and automation
• Build internal tooling to improve data reliability and developer productivity.
• Partner with product, analytics, and engineering teams to define data needs and infrastructure requirements.
• Contribute to cross-functional system design discussions and architectural reviews.
• Ensure delivery of reliable infrastructure and data solutions that meet SLAs.

Quality & Best Practices

• Implement monitoring, alerting, and logging for data pipelines.
• Write automated tests for data transformations and pipeline logic.
• Drive best practices for scalability, cost efficiency, and data governance.

Qualifications

• 4–6 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).

Required Skills

• 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.