Data Engineer III - Senior Associate

Next Frontier Capital; Buenos Aires; Presencial; ARS 183.450.000 - 275.175.000; Jornada completa

Descripción de la vacante

JPMorgan Chase Corporate Sector seeks a Senior Data Engineer (Data Engineer III) focused on AWS and Databricks to build scalable data pipelines and governance. You will lead design, implement, and optimize ETL processes, mentor junior engineers, and collaborate with FinOps for cloud cost strategies.

You will work across data ingestion, storage, and analytics with emphasis on secure, auditable, and resilient data architectures.

Formación

• Strong degree in computer science, engineering, or related field.
• Extensive data lifecycle experience from ingestion to analytics.
• Advanced SQL and working knowledge of NoSQL databases.
• Hands-on AWS data engineering (Lambda, S3, Redshift, RDS, DynamoDB).
• Experience with Terraform or CloudFormation for IaC.
• Proven data governance and security implementation in the cloud.
• Ability to mentor engineers and lead projects with autonomy.
• Experience validating AI-assisted outputs and data handling.

Responsabilidades

• Design, develop, and maintain scalable ETL pipelines in AWS and Databricks.
• Optimize Spark/Delta Lake workflows and data processing.
• Integrate data from diverse sources into Databricks and AWS data stores.
• Collaborate with FinOps to apply cost optimization strategies.
• Mentor junior engineers and guide best practices.
• Ensure data governance, security, and access controls.

Conocimientos

SQL proficiency

NoSQL experience

Python

PySpark

AWS data services

Databricks

Terraform/CloudFormation

Data governance

Security controls

Mentorship

Educación

Bachelor's or Master's in CS/Engineering

Herramientas

Databricks Unity Catalog

Airflow

Spark

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.

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.

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. 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 and technical solutions. Your ideas and contributions will be valued and considered as part of our team’s ongoing innovation.