PySpark / AWS / Databricks / Software Engineer II
- Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
- Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity
- Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
- Adds to team culture of diversity, opportunity, inclusion, and respect
- Implement robust monitoring and alerting systems to proactively identify and address data ingestion issues, optimizing performance and throughput
- Implement data quality checks and validation processes to ensure accuracy and reliability of data
- Design and implement scalable data frameworks to manage end-to-end data pipelines for workforce data analytics
- Share and develop best practices with Platform and Architecture teams to improve data pipeline framework and modernize the workforce data analytics platform
- Formal training or certification on software engineering concepts and 2+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Demonstrable ability to code in one or more languages
- Experience across the whole Software Development Life Cycle
- Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security
- Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Proficiency in data processing frameworks and tools (Parquet, Iceberg, PySpark, Glue, Lambda, AWS, EMR, Athena, and Redshift)
- Proficiency in programming languages (3+ years) such as Python and Scala for data processing and application development
- Experience with scheduling tools (Autosys or Airflow) to automate and manage job scheduling for efficient workflow execution
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
- Proficiency in Relational Databases (Oracle or SQL Server)
- Skilled in writing Oracle SQL queries utilizing (DML, DDL and PL/SQL)
- AWS Certification
- Databricks knowledge
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
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