Director of Software Engineering - Data Platforms & Engineering Lead

If you are a software engineering leader ready to take the reins and drive impact, we've got an opportunity just for you.

As a Director of Software Engineering - Data Platforms & Engineering Lead at JPMorgan Chase within Digital Technology, you lead a technical area and drive impact within teams, technologies, and projects across departments.

Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.

Job responsibilities Leads technology and process implementations to achieve functional technology objectives Oversees decisions that influence teams' resources, budget, tactical operations, and the execution and implementation of processes and procedures Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations Delivers technical solutions that can be leveraged across multiple businesses and domains Influences peer leaders and senior stakeholders across the business, product, and technology teams Champions the firm's culture of diversity, equity, inclusion, and respect Manage agile software delivery teams focus on Full Stack development for Marketing Automation Platforms and partnering with the Area Product & Data owner(s) Deliver solutions leveraging modern technologies utilizing modern design patterns Triage technical issues and lead teams toward solving problems Mentor team members to progress their technical and professional skillsRequired qualifications, capabilities, and skills 10 years of experience managing Software Delivery teams and enterprise products 5 years of managing Java or other full stack technical Delivery teams and enterprise products 5 years of hands-on experience as a Web or Full Stack Developer, as an IT Consultant, or in a related occupation Expertise in one or more big data processing frameworks such as Spark, Flink, Storm etc.

as well as experience with stream processing using Kafka is mandatory Understanding of data design & modeling principles as well as architecture patterns such as data lake, lakehouse, data mart, data fabric and data mesh Experience with Cloud services and cloud native data technologies such as AWS EMR, Glu, Lambda, MSK, RDS, Document DB.

AWS preferred Advanced knowledge of architecture, design, and business processes with proficiency in application, data, and infrastructure architecture disciplines Understanding of modern design patterns used in Java Knowledge and experience using popular build tools, like MAVEN as well as Development Tools Knowledge and experience in TDD and modern testing frameworks that support itPreferred qualifications, capabilities, and skills Understanding of Open / Linked data media types such as RDF, Turtle, JSON-LD, CSV-W Experience with Semantic technologies, modeling, and related concepts such as controlled vocabularies (), ontologies as well as taxonomies Experience with Graph databases such Property Graphs (Neo4J, Datastax Graph) or Semantic / Knowledge Graphs (AWS Neptune) as well as graph processing languages such as Gremlin, Cypher and SparQL is a huge plus Experience with Snowflake or another public cloud is a plus