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JPMorganChase

Senior Lead Software Engineer - AWS, Java/Scala/Python, Spark

Posted 3 Days Ago
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Hybrid
Bengaluru, Karnataka
Senior level
Hybrid
Bengaluru, Karnataka
Senior level
As a Senior Lead Software Engineer, you will design and implement software solutions, collaborate with technical teams, ensure high-quality production code, influence product decisions, and foster a diverse team culture. Your role involves using big data technologies and cloud platforms to drive significant business impact.
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Job Description
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Senior Lead Software Engineer at JPMorgan Chase within the Data Platform Engineering - Corporate Technology organization, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • Drives decisions that influence the product design, application functionality, and technical operations and processes
  • Serves as a function-wide subject matter expert in one or more areas of focus
  • Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies
  • Adds to the team culture of diversity, equity, inclusion, and respect


Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands - on practical experience working in big data environment, working with structured, semi-structured and unstructured data.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced understanding of one or more object-oriented programming language(s) with expertise in languages such as Scala, Java, Python etc.
  • Proficient in building applications for real-time streaming using Apache Spark Streaming, Apache Kafka, Amazon Kinesis etc. for large-scale data processing and open-source frameworks/libraries such as Apache Airflow etc.
  • Proficient in application, data, and infrastructure architecture disciplines.
  • Proficient in cloud-native architecture, design and implementation across all systems.
  • Proficient in Event Driven Architecture and Application Containerization.
  • Proficient in building applications on Public Cloud (AWS, GCP, Azure) development with AWS
  • Proficient in building on emerging cloud server less managed services, to minimize/eliminate physical/virtual server footprint.
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.


Preferred qualifications, capabilities, and skills

  • Proficient in designing and developing data pipelines using Databricks Lakehouse to ingest, enrich, and validate data from multiple sources.
  • Proficient in re-engineering and migrating on-premises data solutions to and for the public cloud.
  • Proficient in implementing security solutions for data storage and processing in the public cloud.
  • Proficient understanding of traditional big data systems, such as Hadoop, Impala, Sqoop, Oozie, Cassandra, Hive, HBase etc.

Top Skills

Amazon Kinesis
Apache Airflow
Apache Kafka
Apache Spark Streaming
AWS
Azure
Cassandra
Databricks
GCP
Hadoop
Hbase
Hive
Impala
Java
Oozie
Python
Scala
Spark
Sqoop

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