Data Platform Engineer

Salt; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Salt is seeking a skilled Data Platform Engineer to build and scale reliable data infrastructure and pipelines that enable analytics, product, and business teams across the organization.

The role requires 4–6 years in data platform or data engineering, strong SQL, and hands-on experience with Airflow, DBT, Spark, or Flink, along with cloud familiarity. You will design data models, implement scalable pipelines, and collaborate with cross-functional teams.

Qualifications

• 4–6 years of experience in data platform or data engineering roles.
• Strong proficiency in SQL.
• 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 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, 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

Programming languages

Data modeling

Tools

Airflow

DBT

Spark

Flink

Kafka

Kinesis

Pub/Sub

AWS

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.