JPMorgan Data Engineer - Cyberops 

United States, Texas, Plano 

251463364

Your contributions will be pivotal in shaping the future of cybersecurity, fostering a culture of excellence, and ensuring the integrity and security of our data infrastructure.

As a Data Engineer at JPMorgan Chase within the Cybersecurity and Technology Controls, you'll leverage your skills to develop and implement robust data solutions using cutting-edge technologies. You'll play a critical role in analyzing complex data structures, ensuring data accuracy, and enhancing our security analytics capabilities. Collaborate with cross-functional teams to drive innovation, implement scalable solutions, and protect our digital assets.

Responsibilities:

• Develop and implement processes and procedures to identify, monitor, and mitigate data risks within the product.
• Design and implement complex, scalable solutions to efficiently process data, ensuring consistent and timely delivery and availability.
• Focus on building robust systems that can handle large volumes of data with minimal downtime.
• Develop solutions using Agile DevOps methodologies and continuous integration/continuous deployment (CI/CD) practices on public cloud platforms.
• Troubleshoot and resolve complex issues related to data architecture, including data ingestion, indexing, and search performance.
• Create reusable frameworks with a strong emphasis on quality and long-term sustainability.
• Perform root cause analysis on data to answer specific business questions or issues.
• Collaborate with key partners to enhance understanding of data usage within the business.
• Serve as a subject matter expert on the content and application of data in the product and related business areas.
• Document and enforce requirements for data accuracy, completeness, and timeliness within the product.
• Integrate data from multiple sources, including structured, semi-structured, and unstructured data, and implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of the data.

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on SQL concepts and 3+ years applied experiencewith data transformation tools such as DBT.
• Proficient in database management, with experience in both relational databases (SQL) and NoSQL databases.
• Minimum 5+ years of experience with Python and SQL.
• Expertise in Python and Java development.
• Extensive experience with Big Data technologies, including Spark, Hive, Redshift, Kafka, and others.
• Excellent understanding of ETL/ELT frameworks and tools, including DBT, Apache Airflow, Trino, Kestra, or similar technologies.
• Hands-on experience in data pipelines and ETL/ELT processes using Python and SQL.
• Experience with Kafka data streaming or other streaming/messaging services like Kinesis, SNS, SQS.
• Demonstrated experience developing, debugging, and tuning complex SQL statements.
• Experience working on real-time and streaming applications, with a solid grasp of agile methodologies, including CI/CD, application resiliency, and security best practices.
• Exceptional understanding of distributed systems and cloud platforms, with expertise in performing data transformations to enhance data quality and usability.

Preferred Qualifications, Capabilities, and Skills:

• Relevant industry experience, preferably in a data engineering role focused on threat detection and security analytics.
• Experience with advanced data streaming and transformation tools.
• Experience with Kubernetes for container orchestration is a plus.
• Be a team player and work collaboratively with team members.