Data Platform Engineer
Summary
Build and scale reliable data infrastructure and pipelines using Python/Java/Go, Spark, Kafka, and cloud platforms to enable analytics and product teams.
About the Role
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.
What You Will Do
- 1. Data Platform & Pipelines
- a. Build and maintain ETL/ELT pipelines for structured and unstructured data.
- b. Design, develop, and optimize batch and streaming pipelines using tools such as Kafka, Spark, or Flink.
- c. Ensure data integrity, availability, and performance across data systems.
- d. Design and optimize data models for analytics and product use cases.
- 2. Backend & Data Engineering
- a. Write clean, maintainable, production-grade code (preferably Python, Java, Go, or Ruby) to support: Data workfl ows Internal data services Integrations and automation
- b. Build internal tooling to improve data reliability and developer productivity.
- 3. Collaboration & Delivery
- a. Partner with product, analytics, and engineering teams to defi ne data needs and infrastructure requirements.
- b. Contribute to cross-functional system design discussions and architectural reviews.
- c. Ensure delivery of reliable infrastructure and data solutions that meet SLAs.
- 4. Quality & Best Practices
- a. Implement monitoring, alerting, and logging for data pipelines.
- b. Write automated tests for data transformations and pipeline logic.
- c. Drive best practices for scalability, cost effi ciency, and data governance.
What You Will Need:
- 1 4-6 years of experience in data platform or data engineering roles.
- Strong profi ciency in SQL and experience with relational and NoSQL databases.
- Hands-on experience with Airfl ow, DBT, Spark, or Flink.
- Experience with streaming or batch data processing systems.
- Profi ciency 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 (Snowfl ake, BigQuery, Redshift).
- Experience operating data platforms in high-scale or fi ntech domains.
- Understanding of data security, privacy, and compliance.