JPMorgan Lead Software Engineer - Data 

United States, Texas, Plano 

991561694

Job responsibilities:

• Provides recommendations and insight on data management, governance procedures, and intricacies applicable to the acquisition, maintenance, validation, quality, anomaly detection and utilization of data​​
• Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
• Defines database back-up, recovery, and archiving strategy
• Generates advanced data models for one or more teams using firmwide tooling, linear algebra, statistics, and geometrical algorithms
• Approves data analysis tools and processes​
• Creates functional and technical documentation supporting best practices​​
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture.
• Design & develop data pipelines end to end using Spark SQL, Java and AWS Services. Utilize programming languages like Java, Python, NoSQL databases, SQL, Container Orchestration services including Kubernetes, and a variety of AWS tools and services.
• Contributes to software engineering communities of practice and events that explore new and emerging technologies
• Evaluates and reports on access control processes to determine effectiveness of data asset security​
• Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills:

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying language.
• Hands-on practical experience in developing spark-based Frameworks for end-to-end ETL, ELT & reporting solutions using key components like Spark SQL & Spark Streaming.
• Proficient in coding in one or more Coding languages - Java, Python
• Experience with Relational and No SQL databases,
• Cloud implementation experience with AWS including:
  • AWS Data Services: Proficiency in Lake formation, Glue ETL (or) EMR, S3, Glue Catalog, Athena, Kinesis (or) MSK, Airflow (or) Lambda + Step Functions + Event Bridge
  • Data De/Serialization: Expertise in at least 2 of the formats: Parquet, Iceberg, AVRO, JSON-LD
  • AWS Data Security: Good Understanding of security concepts such as: Lake formation, IAM, Service roles, Encryption, KMS, Secrets Manager
• Proficiency in automation and continuous delivery methods.
• Solid understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security

Preferred qualifications, capabilities, and skills:

• Snowflake knowledge or experience preferred
• In-depth knowledge of the financial services industry and their IT systems
• Worked with building Data lake, built Data platforms, built Data frameworks, Built/Design of Data as a Service AP