Data Platform Engineer

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
Data Platform & Pipelines
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.
Backend & Data Engineering
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.
Collaboration & Delivery
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.

Work arrangement
No