Data lake Support Associate II - PHL (MID SHIFT)

Key Responsibilities

• Monitor, maintain, and support enterprise data lake environments and data pipelines.
• Troubleshoot and resolve issues related to data ingestion, transformation, and processing.
• Analyze production incidents and perform root cause analysis to prevent recurring issues.
• Support ETL/ELT workflows and ensure data integrity, quality, and availability.
• Collaborate with data engineers and cross-functional teams to implement fixes and enhancements.
• Optimize data processing jobs for performance and reliability.
• Monitor system health, logs, and batch processes to ensure smooth daily operations.
• Document support procedures, issue resolutions, and technical knowledge.
• Participate in incident management and provide timely resolution of production issues.
• Ensure adherence to data governance, security, and operational best practices.

Required Qualifications

• 3-5 years of experience
• Highly preferred: Hands-on expertise with PySpark.
• Experience working with SQL and relational databases.
• Familiarity with ETL/ELT processes and data pipeline troubleshooting.
• Knowledge of cloud-based data platforms (Azure, AWS, or GCP) is an advantage.
• Experience with distributed data processing frameworks such as Apache Spark.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication skills with the ability to work effectively in a global team.

Preferred Skills

• PySpark (Highly Preferred)
• Apache Spark
• SQL
• Python
• Data Lake technologies
• ETL/ELT Support
• Incident Management
• Data Quality Monitoring
• Cloud Data Platforms (Azure, AWS, or GCP)

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Work Schedule & Setup

• Shift: 9:00 AM – 6:00 PM CEST (Paris Time) / 3:00 PM – 12:00 AM Manila Time
• Work Setup: Hybrid (1 day onsite per week)

Interview Process

• 1 Round of Interview

Client - WTW

Employment Type: 6mos to 1 year project-based contract subject for extension or absorption depending on performance.

Note: Don't apply if you're unsure regarding the details (employment type, set-up, and schedule). Think thoroughly before applying.