The Data Engineer II role involves designing, developing, and maintaining cloud-based data pipelines, optimizing data models, and collaborating with teams to enhance data engineering solutions.
Job Description
We have an exciting and rewarding opportunity for you to take your Data Engineer career to the next level.
As a Data Engineer II at JPMorganChase within Consumer & Community Banking in Connected Commerce Travel Technology Team, you will be the part of an agile team that designs, builds and maintains cutting-edge large-scale data integration and analytical solutions on the cloud in a secure, stable, and scalable way. In this role, you'll leverage your technical expertise and business acumen to transform complex, high-volume data into powerful, actionable insights, driving strategic value for our stakeholders. This is an exciting opportunity to shape the future of how Chase Travel data is managed for analytical needs.
Job responsibilities
Required qualifications, capabilities, and skills
Preferred qualifications, capabilities, and skills
We have an exciting and rewarding opportunity for you to take your Data Engineer career to the next level.
As a Data Engineer II at JPMorganChase within Consumer & Community Banking in Connected Commerce Travel Technology Team, you will be the part of an agile team that designs, builds and maintains cutting-edge large-scale data integration and analytical solutions on the cloud in a secure, stable, and scalable way. In this role, you'll leverage your technical expertise and business acumen to transform complex, high-volume data into powerful, actionable insights, driving strategic value for our stakeholders. This is an exciting opportunity to shape the future of how Chase Travel data is managed for analytical needs.
Job responsibilities
- Design, develop and maintain scalable and large-scale data processing pipelines and infrastructure on the cloud following engineering standards, governance standards and technology best practices
- Develop and optimize data models for large-scale datasets, ensuring efficient storage, retrieval, and analytics while maintaining data integrity and quality.
- Collaborate with cross-functional teams to translate business requirements into scalable and effective data engineering solutions.
- Demonstrate a passion for innovation and continuous improvement in data engineering, proactively identifying opportunities to enhance data infrastructure, data processing and analytics capabilities.
Required qualifications, capabilities, and skills
- Strong analytical problem solving and critical thinking skills
- Proficiency in at least one programming language ( Python, if not Java or Scala)
- Proficiency in at least one distributed data processing framework ( Spark or similar)
- Proficiency in at least one cloud data Lakehouse platforms (AWS Data lake services or Databricks, alternatively Hadoop),
- Proficiency in at least one scheduling/orchestration tools ( Airflow, if not AWS Step Functions or similar)
- Proficiency with relational and NoSQL databases.
- Proficiency in data structures, data serialization formats (JSON, AVRO, Protobuf, or similar), and big-data storage formats (Parquet, Iceberg, or similar),
- Experience working in teams following Agile methodology
- Experience with test-driven development (TDD) or behavior-driven development (BDD) practices, as well as working with continuous integration and continuous deployment (CI/CD) tools.
Preferred qualifications, capabilities, and skills
- Proficiency in Python and Pyspark
- Proficiency in IaC (preferably Terraform, alternatively AWS cloud formation)
- Experience with AWS Glue, AWS S3, AWS Lakehouse, AWS Athena, Airflow, Kinesis and Apache Iceberg
- Experience working with Jenkins
Top Skills
Airflow
Apache Iceberg
Avro
Aws Athena
Aws Cloud Formation
Aws Data Lake Services
Aws Glue
Aws Lakehouse
Aws S3
Aws Step Functions
Databricks
Hadoop
Iceberg
Java
Jenkins
JSON
Kinesis
Nosql Databases
Parquet
Protobuf
Python
Relational Databases
Scala
Spark
Terraform
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