Data Engineer [Multiple Positions Available]

JPMorgan Chase & Co. • Plano, TX

4h • Onsite

About The Position

Duties: Perform solution architecture, and design and develop data ingestion processes for Machine Learning pipelines. Evaluate new and current technologies using emerging model feature engineering standards and frameworks. Provide technical guidance and direction to support the business and its technical teams, contractors, and vendors. Contribute to the engineering community as an advocate of firm-wide data frameworks, tools, and practices in the AI and ML Development Life Cycle. Influence peers and project decision-makers to consider the use and application of leading-edge technologies. Apply advanced analytics techniques to identify, analyze, and interpret trends or patterns in complex data sets enabling superior machine learning model outcomes. Innovate new ways of managing, transforming, and validating Machine learning model outputs. Establish and enforce guidelines to ensure consistency, quality, and completeness of Machine learning feature data assets. Act as the coach and mentor to team members on their assigned project tasks. Develop a cohesive MLOps and DataOps pipeline to ensure scalability, reliability and resiliency. Conduct product work reviews with team members.

Requirements

• Bachelor's degree in Electronic Engineering, Computer Engineering, Computer Science or related field of study plus 7 years of experience in the job offered or as Data Engineer, IT Project Architect, IT Consultant, Application Developer, Software Engineer, or related occupation.
• seven (7) years of experience with the following: utilizing Data Lake and Delta Lake Management Architecture for AI and ML enablement
• seven (7) years of experience with: designing and implementing data lake management architecture for AI-driven solutions, including both traditional Data Lakes and Delta Lakes for optimized data storage and processing
• seven (7) years of experience with: technology, big data analysis, and ML features domain consulting
• seven (7) years of experience with: analyzing, designing, and conducting proof of concepts (POC) to validate architectural decisions and data strategies
• seven (7) years of experience with: delivering incremental solutions using an Agile approach, ensuring continuous integration and delivery
• seven (7) years of experience with: implementing transformations on big data platforms, Python, PySpark and Scala programming languages, including NoSQL databases, Teradata, DB2, Hadoop, Snowflake and SAS BI tools with a focus on leveraging Delta Lake for ACID transactions and scalable data processing.
• five (5) years of experience with the following: utilizing Databricks and AWS and Azure data processing tools to support ML model training
• five (5) years of experience with the following: utilizing data transformation tools including AWS Glue, EMR, EKS, Redshift, MSK (Managed Streaming for Apache Kafka), AWS Kinesis, and Databricks for collaborative data engineering and machine learning workflows
• five (5) years of experience with the following: handling terabyte- sized datasets with multi-threading in PySpark on cloud platforms, utilizing Databricks for enhanced performance and scalability
• five (5) years of experience with the following: utilizing cloud computing platforms including Azure or AWS, integrating Databricks for seamless data processing and analytics
• three (3) years of experience with the following: using event-driven architecture (EDA) and real-time streaming to identify fraud proactively
• three (3) years of experience with the following: utilizing event-driven architecture using event streaming with Apache Kafka and AWS MSK for real-time feature engineering
• three (3) years of experience with the following: developing end-to- end pipelines using Python and PySpark to support Data Lake, Data warehouse and ML models, leveraging Databricks for model training and deployment.
• one (1) year of experience with the following: applying data exploration techniques to analyze customer behavior to find actionable domain specific insights utilizing algorithms to explore large collection of customer transactions and reveal hidden relationships among entities, ensuring comprehensive data insights
• one (1) year of experience with the following: maintaining governance, reproducibility, and scalability of models, while optimizing workflows for efficiency
• any amount of experience with the following: utilizing AWS Kinesis for real-time data streaming and processing, to ensure low-latency and high-throughput data pipelines.

Responsibilities

• Perform solution architecture, and design and develop data ingestion processes for Machine Learning pipelines.
• Evaluate new and current technologies using emerging model feature engineering standards and frameworks.
• Provide technical guidance and direction to support the business and its technical teams, contractors, and vendors.
• Contribute to the engineering community as an advocate of firm-wide data frameworks, tools, and practices in the AI and ML Development Life Cycle.
• Influence peers and project decision-makers to consider the use and application of leading-edge technologies.
• Apply advanced analytics techniques to identify, analyze, and interpret trends or patterns in complex data sets enabling superior machine learning model outcomes.
• Innovate new ways of managing, transforming, and validating Machine learning model outputs.
• Establish and enforce guidelines to ensure consistency, quality, and completeness of Machine learning feature data assets.
• Act as the coach and mentor to team members on their assigned project tasks.
• Develop a cohesive MLOps and DataOps pipeline to ensure scalability, reliability and resiliency.
• Conduct product work reviews with team members.

Benefits

• We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location.
• Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
• We also offer a range of benefits and programs to meet employee needs, based on eligibility.
• These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level