Data Engineer

Technical Stack & Requirements:

• Core Competencies: Python, Apache Spark (PySpark), AWS Glue ETL, Data Lake concepts (Medallion Architecture).
• Infrastructure: CloudFormation/Terraform, CI/CD with GitHub Actions.
• Core Responsibilities: Orchestrate data extraction from diverse legacy and modern sources, engineer high-performance scalable pipelines, and provide expert-level production support to ensure system reliability.

Qualifications:

• Bachelor’s degree in Computer Science or related field.
• Strong hands-on experience with Apache Spark and Glue.
• Proven ability to work with Python-based data pipelines.
• Experience with Git and GitHub Actions is mandatory.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related discipline.
• 7 years of enterprise Data Engineering experience.
• Strong Python development experience.
• Advanced SQL programming skills.
• Extensive experience with Apache Spark and PySpark.
• Hands-on experience with AWS data services including:
  • S3
  • AWS Glue
  • Athena
  • Lambda
  • Step Functions
  • EventBridge
• Experience building enterprise ETL and ELT pipelines.
• Strong understanding of distributed data processing.
• Experience working with large-scale cloud data platforms.
• Strong knowledge of dimensional data modeling.
• Experience implementing CI/CD pipelines.
• Familiarity with Agile/Scrum methodologies.
• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Financial Services or Asset Management industry experience.
• Experience with Snowflake or Databricks.
• Knowledge of Apache Iceberg, Delta Lake, or Hudi.
• Experience with Airflow.
• Knowledge of Kafka or Kinesis streaming.
• Experience supporting AI/ML and advanced analytics platforms.
• AWS Professional or Specialty Certifications.