Description

You will design, develop, and maintain scalable ETL/ELT pipelines and Lakehouse architectures.

This role is on-site.

Responsibilities

• Design and maintain scalable ETL/ELT pipelines using Scala and Apache Spark or Flink for batch and streaming workloads.
• Optimize Spark jobs and SQL queries to improve performance, efficiency, and cost.
• Implement Lakehouse architectures using Apache Iceberg, Hudi, or Delta Lake, applying Medallion Architecture (Bronze/Silver/Gold).
• Enable data observability to ensure data freshness, lineage, and reliability.

Required Skills

• Strong proficiency in Scala and Apache Spark (Batch & Streaming).
• Solid understanding of SQL and distributed computing concepts.
• Experience with GCP (Dataproc, GCS, BigQuery) or equivalent cloud platforms (AWS/Azure).
• Hands-on experience with Docker and Kubernetes.
• Experience with Lakehouse table formats (Iceberg, Hudi, Delta).
• Familiarity with CI/CD practices.
• Bachelor's degree required.
• 1–5 years of experience as a Data Engineer or Big Data Engineer.

Preferred Skills

• Experience building data pipelines for ML or feature engineering.
• Exposure to workflow orchestration tools such as Airflow or Azkaban.

Key Skills

Education

Bachelor's degree