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JPMorgan Data Engineer lll 
India, Telangana, Hyderabad 
8857712

06.07.2024

Job responsibilities

  • Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
  • Creates secure and high-quality production code.
  • Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development.
  • Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems.
  • 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.
  • Adds to team culture of diversity, equity, inclusion, and respect.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3+ years of 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 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, Scala, 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 Manage
Preferred qualifications, capabilities, and skills
  • Proficiency in automation and continuous delivery methods.
  • Experience in Snowflake nice to have.
  • Proficient in all aspects of the Software Development Life Cycle.
  • Solid understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security.
  • In-depth knowledge of the financial services industry and their IT systems. Practical cloud native experience preferably AWS.