Job description

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.

Requirements

Must-haves

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.
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.
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
Step Functions
Experience building enterprise ETL and ELT pipelines.
Strong understanding of distributed data processing.
Experience working with large-scale cloud data platforms.

Nice-to-haves

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonawsci/cdsqlagilescrumaiml

Platform: jobdiva
Effort: medium