Description

Architect and build enterprise-scale distributed data platforms and high-performance pipelines.

This role is on-site.

Responsibilities

• Architect enterprise-scale distributed data platforms and data lakehouse solutions using Apache Iceberg.
• Build high-performance data pipelines using PySpark and Spark SQL.
• Develop federated query architectures with Trino (Presto) and design modern data lakehouse structures.
• Lead cloud migration and data modernization initiatives across AWS, Azure, or GCP.
• Mentor engineering teams and drive technical best practices in CI/CD, Git, and DevOps.

Required Skills

• 10+ years of experience in data engineering and distributed systems.
• Expert-level proficiency with PySpark and Spark SQL.
• Deep experience with Apache Iceberg for data lakehouse architectures.
• Strong knowledge of Trino (Presto) for federated querying.
• Proficiency with cloud platforms: AWS, Azure, or GCP.
• Experience with Airflow, Parquet, ORC, and Avro.
• Strong SQL and data modeling skills.
• Familiarity with CI/CD, Git, and DevOps practices.

Preferred Skills

• Enterprise architecture experience.
• Customer-facing consulting or solution design background.
• Exposure to AI/ML and analytics platforms.

Key Skills

Education

Not specified