Position Title: Senior Data/Big Data Engineer
Location: New York, NY- Onsite
Duration: 6-month (Contract to hire)
Client Name: JPMorgan Chase
Interview : Onsite
Must Have:
- 5 10+ years of Big Data Engineering experience.
- Expert-level Python programming.
- Strong Apache Spark.
- Solid Data Structures & Algorithms.
- Experience building large-scale distributed applications.
- Experience with AWS EMR and Glue ETL
- Strong software engineering fundamentals with system design capability.
- Ability to confidently explain every technology and project listed on their resume.
- Excellent collaboration skills and the ability to contribute to a long-term engineering team.
Job Responsibilities
As a Lead Software Engineer at Client within Consumer & Community Banking Open Banking team, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm s business objectives.
Job responsibilities
- Architect and oversee the design of complex data solutions that meet diverse business needs and customer requirements.
- Guide the evolution of logical and physical data models to support emerging business use cases and technological advancements.
- Build and manage end-to-end cloud-native data pipelines in AWS, leveraging your hands-on expertise with AWS components.
- Build analytical systems from the ground up, providing architectural direction, translating business issues into specific requirements, and identifying appropriate data to support solutions.
- Work across the Service Delivery Lifecycle on engineering major/minor enhancements and ongoing maintenance of existing applications.
- Conduct feasibility studies, capacity planning, and process redesign/re-engineering of complex integration solutions.
- Help others build code to extract raw data, coach the team on techniques to validate its quality, and apply your deep data knowledge to ensure the correct data is ingested across the pipeline.
- Guide the development of data tools used to transform, manage, and access data, and advise the team on writing and validating code to test the storage and availability of data platforms for resilience.
- Oversee the implementation of performance monitoring protocols across data pipelines, coaching the team on building visualizations and aggregations to monitor pipeline health.
- Coach others on implementing solutions and self-healing processes that minimize points of failure across multiple product features.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Extensive experience in managing the full lifecycle of data, from collection and storage to analysis and reporting.
- Proficiency in one or more large-scale data processing distributions such as Java or Python Spark along with knowledge on Data Pipeline (DPL), Data Modeling, Data warehouse, Data Migration and so-on.
- 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.
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Strong organizational, problem-solving, and critical thinking skills; Strong documentation skills
- Proficiency in Python or Java and proficiency in Spark
- Hands-on experience on AWS services and its components along with good understanding on Kubernetes. 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-L
- AWS Data Security: Good Understanding of security concepts such as: Lake formation, IAM, Service roles, Encryption, KMS, Secrets Manager
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Experience designing and building REST API services using Java
- Exposure to cloud technologies - knowledge on Hybrid cloud architectures
- DevOps: Linux Scripting, Jenkins, Git, CI/CD, JIRA, TDD skills
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