Description

Develop data processing solutions using PySpark within a financial data context.

Responsibilities

• Build and maintain data pipelines using Scala, Python, and PySpark.
• Process complex financial datasets including income statements, balance sheets, and cash flow statements.
• Implement models for discounted cash flow (DCF) analysis, leveraged buyout (LBO), mergers and acquisitions (M&A), and sensitivity analysis.
• Manage data workflows across AWS and Azure Databricks environments.

Required Skills

• 5+ years of professional experience in data engineering.
• Proficiency in Python, PySpark, and Scala.
• Strong SQL and PL/SQL skills.
• Experience with Linux shell scripting.
• Hands-on experience with Amazon EC2 and S3.
• Experience working with Azure Databricks.
• Mandatory experience handling financial data.
• Knowledge of the Hadoop Ecosystem including HDFS, YARN, Hive, HBase, Impala, ZooKeeper, Sqoop, Oozie, Drill, Flume, Solr, and Avro.

Key Skills

Education

Any Graduate