Description

You will design and lead large-scale data platform transformations from legacy systems to modern analytical environments.

Responsibilities

• Architect Cloudera and Hadoop-based platforms capable of managing petabytes of data.
• Lead code migration engagements, specifically moving workloads from DataStage to PySpark.
• Optimize job performance and workload management across large Hadoop clusters running thousands of concurrent jobs.
• Build frameworks for data transformation and code quality.
• Drive technical strategy and solutioning through direct conversations with Director, SVP, and senior leadership.

Required Skills

• 12+ years of experience in data engineering or architecture.
• Hands-on expertise with Cloudera and Hadoop ecosystems.
• Deep knowledge of PySpark, Hive, and Big Data technologies.
• Proven experience with ETL tools like Talend and visualization via Tableau.
• Expertise in large-scale data warehousing concepts.
• Demonstrated ability to manage petabyte-scale data environments.
• Experience performing performance optimization for long-running Big Data jobs.
• Background in banking industry projects involving regulatory compliance.

Preferred Skills

• Any Graduate degree.

Key Skills

Education

Any Graduate