Data Engineer - I

A Data Engineer I at GoKwik will design, build, and maintain end‑to‑end data pipelines that support analytics, machine learning models, and business applications. The role involves working with modern data engineering technologies such as Apache Iceberg, Trino, Spark, and Kubernetes, and requires a strong focus on data quality, performance, and cost optimization.

• Design, build, and maintain end‑to‑end data pipelines, from source ingestion to production‑ready data models
• Develop reliable and reusable data transformation workflows using SQL, Python, Trino, and Spark
• Implement incremental data processing, MERGE operations, and idempotent jobs for efficient delivery
• Onboard new data sources and migrate legacy pipelines to standardized frameworks
• Implement data quality checks, validation rules, deduplication logic, and safeguards for edge cases
• Build monitoring and alerting mechanisms to detect data issues before downstream impact
• Analyze and optimize SQL queries and distributed data processing jobs for performance and cost efficiency
• Investigate production issues, conduct root‑cause analysis, and implement long‑term fixes
• Collaborate with Engineering, Analytics, and Data Science teams to resolve data‑related issues
• Contribute to data platform engineering, including orchestration, infrastructure, and deployment workflows
• Explore real‑time data serving and analytical systems using Apache Pinot and ClickHouse
• Support data governance, documentation, and standardization initiatives
• Use AI‑assisted development tools to improve productivity while validating generated code and queries

• 1–3 years of experience building data pipelines or data platform systems
• Strong SQL skills and ability to debug queries
• Solid Python programming skills; experience with PySpark is an advantage
• Hands‑on experience with at least one distributed data processing or query engine (Spark, Trino, or Hive)
• Understanding of data warehousing and lakehouse fundamentals, including facts, dimensions, partitioning, and incremental loads
• Strong debugging mindset and ability to identify root causes
• Comfortable writing tests, participating in code reviews, and following software engineering best practices
• Clear communication of technical issues and effective collaboration with cross‑functional teams
• Experience using AI development tools to improve productivity while validating outputs
• Curiosity, ownership, and willingness to learn modern data platform technologies