Data Engineer III - Senior Associate

JPMorganChase; Buenos Aires; Presencial; ARS 2.500.000 - 4.500.000; Jornada completa

Descripción de la vacante

JPMorgan Chase Corporate Sector is seeking a Senior Data Engineer to design and deliver trusted data pipelines in a secure, scalable environment with a focus on AWS and Databricks. You will lead projects, mentor junior engineers, and collaborate with FinOps to optimize cloud costs while ensuring data governance and strong validation practices.

The role emphasizes autonomous project leadership, robust data governance, and the ability to translate business needs into scalable, compliant data

Formación

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• Extensive experience across the data lifecycle, including data ingestion, transformation, storage, and analytics.
• Advanced proficiency in SQL (joins, aggregations) and working understanding of NoSQL databases.
• Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns.
• Hands-on experience with AWS data engineering services (Lambda, S3, Redshift, RDS, DynamoDB).
• Experience implementing data governance and security controls in cloud environments.
• Proficiency in workflow orchestration and automation (AWS Step Functions, Airflow).
• Experience with infrastructure as code (Terraform, CloudFormation).
• Strong problem-solving, communication, and collaboration skills.
• Ability to mentor junior engineers technically and lead projects with autonomy.
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs (e.g., query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements.
• Advanced English skills

Responsabilidades

• Design, develop, and maintain scalable ETL pipelines using AWS services (Lambda, Step Functions, S3) and Databricks (Python, PySpark, SQL).
• Optimize data processing workflows leveraging Apache Spark and Delta Lake within Databricks.
• Integrate data from various sources (S3, databases, APIs) into Databricks and AWS data stores.
• Implement and manage data governance, security controls, and access policies using AWS IAM, encryption, and Databricks Unity Catalog.
• Monitor, troubleshoot, and tune data pipelines for performance and reliability.
• Automate infrastructure provisioning and deployment using Terraform or AWS CloudFormation.
• Collaborate with cross-functional teams using Databricks Repos and version control tools.
• Work closely with FinOps professionals to apply cost optimization strategies and best practices in cloud environments.
• Mentor junior engineers and provide technical guidance within the team.
• Update logical or physical data models based on new use cases.
• Advise colleagues on data engineering best practices and tool configurations.
• Communicate complex technical concepts to non-technical stakeholders.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data pipeline/design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Applies reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (e.g., test generation and control validation), ensuring traceability/auditability and alignment to resiliency and security expectations.

Conocimientos

SQL proficiency

AWS data engineering

Databricks

Spark

Terraform/CloudFormation

Mentor/lead projects

English communication

Educación

Bachelor's or Master's degree in CS/Engineering/related field

Herramientas

Databricks

AWS services

S3

Redshift/RDS

DynamoDB

Terraform/CloudFormation

Descripción del empleo

Senior Data Engineer (Data Engineer III) – AWS & Databricks Focus

As a Data Engineer III at JPMorgan Chase Corporate Sector, you will be a key member of our agile Data Engineering team, designing and delivering trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You will develop, test, and maintain critical data pipelines and architectures supporting the firm’s business objectives, with a primary focus on AWS Data Engineering and Databricks.

In this role, you will have autonomy to lead projects, mentor junior engineers, and collaborate closely with FinOps professionals to translate cost optimization strategies into technical solutions. Your ideas and contributions will be valued and considered as part of our team's ongoing innovation.

Job Responsibilities

• Design, develop, and maintain scalable ETL pipelines using AWS services (Lambda, Step Functions, S3 storage) and Databricks (Python, PySpark, SQL).
• Optimize data processing workflows leveraging Apache Spark and Delta Lake within Databricks.
• Integrate data from various sources (S3, databases, APIs) into Databricks and AWS data stores.
• Implement and manage data governance, security controls, and access policies using AWS IAM, encryption, and Databricks Unity Catalog.
• Monitor, troubleshoot, and tune data pipelines for performance and reliability.
• Automate infrastructure provisioning and deployment using Terraform or AWS CloudFormation.
• Collaborate with cross-functional teams using Databricks Repos and version control tools.
• Work closely with FinOps professionals to apply cost optimization strategies and best practices in cloud environments.
• Mentor junior engineers and provide technical guidance within the team.
• Update logical or physical data models based on new use cases.
• Advise colleagues on data engineering best practices and tool configurations.
• Communicate complex technical concepts to non-technical stakeholders.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data pipeline/design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Applies reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (e.g., test generation and control validation), ensuring traceability/auditability and alignment to resiliency and security expectations.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• Extensive experience across the data lifecycle, including data ingestion, transformation, storage, and analytics.
• Advanced proficiency in SQL (joins, aggregations) and working understanding of NoSQL databases.
• Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns.
• Hands-on experience with AWS data engineering services (Lambda, S3, Redshift, RDS, DynamoDB).
• Experience implementing data governance and security controls in cloud environments.
• Proficiency in workflow orchestration and automation (AWS Step Functions, Airflow).
• Experience with infrastructure as code (Terraform, CloudFormation).
• Strong problem-solving, communication, and collaboration skills.
• Ability to mentor junior engineers technically and lead projects with autonomy.
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs (e.g., query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements.
• Advanced English skills

Preferred Qualifications

• Experience with Databricks, including ETL development, Spark optimization, and Delta Lake.
• Familiarity with Databricks Unity Catalog and Repos.
• Notion of FinOps and cloud cost optimization; willingness to work closely with FinOps professionals.
• Experience with monitoring tools (AWS CloudWatch, CloudTrail) and cost management dashboards.
• Financial services industry experience is a plus.

About Us

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

About The Team

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.