Head of Data
1 month ago
We’re creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. As a Data Principal Software Engineer at JPMorgan Chase within the International Consumer Bank, you are the heart of this venture, focused on getting smart ideas into the hands of our customers. You thrive in working in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.
We understand that everyone's unique – and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. Architect and implementation: Design and develop scalable, cost-effective, and secure distributed architectures and solutions, utilizing appropriate GCP and AWS services and technologies.
Lead, manage & mentor a small team of data engineers to design, develop, and implement data platforms, pipelines, and infrastructure for our multi-cloud product across GCP and AWS.
Data pipeline development: Design, implement, and maintain data pipelines that efficiently collect, process, and store large volumes of data from various sources, ensuring data quality and integrity.
Performance optimization: Continuously monitor, analyze, and optimize data pipelines to improve performance, reduce costs, and ensure reliability and scalability.
Ensure that data solutions comply with relevant data security and privacy regulations, and implement best practices for securing data at rest and in transit.
Establish & govern a project wide data catalogue where we maintain the list of all data sets across the platform with the appropriate description of the data items
Programming languages: Actively writing code & proficiency in one or more languages commonly used in data engineering , such as Python, R, Java, or Scala. Data engineering skills: Proficiency in designing, building, developing, and optimizing data pipelines, as well as experience with big data processing tools like Apache Spark, Hadoop, and Dataflow
Experience in designing & operating Operational Datastore/Data Lake/Data Warehouse platforms at scale with high-availability
Data integration: Familiarity with data integration tools and techniques, including ETL (Extract, Transform, Load) processes and real-time data streaming (e.g., using Apache Kafka, Kinesis, or Pub/Sub), exposing data sets via GraphQL
Deep understanding of GCP/AWS services, architectures, and best practices, with hands-on experience in designing and implementing scalable and cost-effective solutions. Data storage and databases: Knowledge of various data storage options (e.g., relational databases, NoSQL, data lakes) and hands-on experience with managing and optimizing databases such as PostgreSQL, MySQL, BigQuery, and Redshift
We want you to coach other team members on coding practices, design principles, and implementation patterns
Comfortable in uncharted waters. We are building something new. Ability to see the long term.
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