Buenos Aires, Buenos Aires, Argentina
Full time
R
Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Job Description
**GBS Chevron Global Business Services (GBS), located in Buenos Aires (Puerto Madero), Argentina, is accepting applications for the position of Data Engineer.
Successful candidates will join the IT Organization, which is part of a multifunction service and technical center with a workforce of more than **** employees that deliver business services and solutions to the corporation across the globe.
**
Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Responsibilities include:
+ Understand business use of data and stakeholder requirements to support work processes and strategic business objectives
+ Leverage data, software engineering, and data science techniques to create business value through data accessibility.
Includes data ingestion, data preparation and analytics processing.
+ Identify, acquire, cleanse & prepare, store data and develop data products aligned with defined architecture patterns
+ Responsible for normalizing and ingesting data from multiple sources.
+ Enable data scientists, making data available for advanced analytics models, and contributing to models.
+ Work with ML Engineer to scale and deploy solution including model, documentation, training, integration
+ Contributing to the inner source development of foundational tools, and/or the deployment of technical services.
Required Qualifications:
+ BS in Computer Science, Management Information Systems, Computer Engineer or related fields or equivalent experience.
+ +5 years in Data Engineer Role
+ Knowledge and/or experience with: data acquisition, preparation and validation; data movement and transformation; analytics solution architecture; big data computing; cloud computing, core data architecture; information security technologies and software engineering using technologies such as: Azure Data Factory (ETL), Databricks, DevOps, CI/CD Pipeline Deployment, Python, Java, Ansible, Azure SQL, Azure Synapse, GIT, ADO, Azure Data Lake, Azure Analysis Services, Logic Apps, Microsoft Data Flows, Kimball Data Warehousing Methodology
+ Analytical thinking, Consulting, Critical Thinking
**Relocation Options:**
Relocation **may be** considered.
**International Considerations:**
Expatriate assignments **will not be** considered
**Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position**
Chevron participates in E-Verify in certain locations as required by law.
Chevron Corporation is one of the world's leading integrated energy companies.
Through its subsidiaries that conduct business worldwide, the company is involved in virtually every facet of the energy industry.
Chevron explores for, produces and transports crude oil and natural gas; refines, markets and distributes transportation fuels and lubricants; manufactures and sells petrochemicals and additives; generates power; and develops and deploys technologies that enhance business value in every aspect of the company's operations.
Chevron is based in Houston, Texas.
More information about Chevron is available at .
Chevron is an Equal Opportunity / Affinit**
Why Join Us
**
**
Mission
**
The Company At Spartan Investment Group our mission is to improve lives through our values.
We do this by finding value-add and opportunistic investments offering solid returns to our investors.
Providing an opportunity to grow for our partners and creating lasting wealth for everyone with whom we conduct business is how we make our greatest contribution.
We specifically focus on self-storage projects capitalizing on amazing deals in other asset classes.
In ****, we were listed as the 5th fastest growing real estate company in the US and joined the list of the top 100 owners of self-storage.
We are members of the Inc.
**** fastest-growing private companies in America and in **** we were #13 in Denver Business Journals list of top places to work.
Mission As the Data Engineer you will design, build, and optimize scalable data infrastructure that powers marketing, business intelligence, and strategic decision-making across the organization.
You will develop reliable data pipelines, integrate third-party platforms, and transform raw data into actionable insights through automation, analytics, and visualization.
Working closely with cross-functional teams, you will ensure data is accurate, accessible, and optimized for performance while continuously identifying opportunities to improve processes and capabilities.
This role combines technical expertise, innovation, and collaboration to deliver high-quality data solutions that support business growth.
Outcomes Data Pipeline Development – Design, build, and optimize end-to-end data pipelines from ingestion through transformation and visualization, delivering scalable, reliable solutions that achieve 99%+ successful pipeline execution.
Platform Integrations – Integrate third-party tools and platforms, including CRMs, MarTech platforms, and custom applications, using APIs, webhooks, and modern integration methods while maintaining reliable data synchronization.
ETL/ELT Optimization – Develop, improve, and maintain ETL/ELT workflows that ensure clean, accurate, and scalable data processing while minimizing failures and manual intervention.
Data Analysis & Insights – Conduct in-depth data and trend analysis to deliver actionable insights that support data-driven marketing strategies and business decision-making.
Cross-Functional Collaboration – Partner with marketing, data,



and business intelligence teams to deliver technical solutions that align with business objectives while meeting project timelines and stakeholder expectations.
Data Warehouse Performance – Optimize data storage and retrieval performance across platforms such as BigQuery, Snowflake, or Azure Synapse to improve query efficiency, scalability, and data accessibility.
Business Intelligence Reporting – Create and maintain Power BI and other business intelligence dashboards that provide accurate, timely reporting and actionable insights for stakeholders.
Continuous Improvement & Ownership – Continuously identify opportunities to improve workflows, reporting, and data capabilities while independently managing priorities, communicating progress transparently, and consistently delivering high-quality solutions Qualifications 2+ years of experience as a Data Engineer, MarTech Developer, or similar role.
Proficiency in Python and SQL for data engineering, automation, and analytics.
Experience designing, building, and optimizing end-to-end ETL/ELT data pipelines.
Experience developing and maintaining REST APIs, webhooks, and third-party system integrations.
Knowledge of data modeling, data architecture, and data integration best practices.
Experience working with Google BigQuery, Data Lake environments, or similar cloud-based data platforms.
Experience creating reports and dashboards using Power BI, Tableau, or similar business intelligence tools.
Experience with Snowflake, Azure Synapse, or other cloud-based data warehouse platforms preferred.
Experience automating workflows using scripting tools, Zapier, or custom automation solutions preferred.
Experience developing chatbot, Generative AI, or machine learning solutions preferred.
Experience supporting marketing technology (MarTech), CRM, or business intelligence ecosystems preferred.
Ability to work full-time and maintain significant overlap with U.S. business hours, including evening or overnight schedules as needed.
Remote Work Requirements Dedicated home office or professional remote work environment.
Reliable high-speed internet connection capable of supporting video conferencing and daily business operations.
LangChain.
LangGraph.
AWS.
We have an exciting and rewarding opportunity for you to take your data engineering career to the next level.
What You Will Do
As a Data Engineer III at JPMorgan Chase within the Commercial & Investment Bank, you are part of an agile team that works to enhance, design, and deliver the software components of the firm's state-of-the‐art technology products in a secure, stable, and scalable way.
As a seasoned member of our Tech Risk & Controls Services team you design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way.
You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm's business objectives.
Job Responsibilities
Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Collaborates with software engineers and teams to design, develop, test, and implement availability, reliability, scalability, and solutions in their applications
Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way.
Supports review of controls to ensure sufficient protection of enterprise data
Contributes to data and software engineering communities of practice and events that explore new and emerging technologies
Required Qualifications, Capabilities, and Skills
Formal training or relevant data engineering certification and 5+ years applied experience
Experience in Qlik Sense in both ETL and Dashboard development
In depth knowledge of Qliksense scripting, QVD Files, Set Analysis
Practical experience in full stack projects, hands‐on mainly with backend technologies such as Java, Spring Boot, JPA (Java Persistence API) Spring Data Repositories
Experience in developing, debugging, and maintaining code in a corporate ecosystem with one or more modern programming languages and database querying languages
Exposure to agile methodologies such as CI/CD, Application Resiliency, and Cybersecurity best practices
Experience with SQL relational DB technologies such as MySQL, Oracle RDMS.
Preferred Qualifications, Capabilities, and Skills
Knowledge of Web Frameworks (. React) will be an added advantage.
Exposure to public cloud technologies, AWS/GCP/Azure experience or certifications is a plus
Experience in observability, monitoring, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, and others.
Familiarity with industry‐wide technology trends and best practices
Argentina Full‐time
Job Description
AgileEngine is an Inc. **** company that creates award‐winning software for Fortune 500 brands and trailblazing startups across 17+ industries.
We rank among the leaders in areas like application development and AI/ML, and our people‐first culture has earned us multiple Best Place to Work awards.
Why Join Us
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
About the Role
We are looking for a
Senior Data Engineer




to operate and improve a Snowflake‐based enterprise data platform in a regulated healthcare environment.
MUST HAVES
-
5+ years
of professional experience in Data Engineering or Data Platform Engineering.
- Strong hands‐on experience operating and developing solutions on
Snowflake
, including data‐layer design, warehouse performance, access patterns, and production troubleshooting.
-
Advanced SQL
skills and strong experience with
dbt
for transformation, testing, documentation, lineage, and controlled deployment.
- Experience operating managed ingestion tools such as
Fivetran
or
HVR
and supporting custom data‐ingestion pipelines.
- Hands‐on experience with
AWS data services
, particularly S3 and event‐driven or file‐based ingestion patterns.
- Experience orchestrating and troubleshooting data workloads with
Argo Workflows on Kubernetes
, or comparable workflow‐orchestration technologies.
- Proficiency in
Python
or a comparable language for data engineering, automation, and operational tooling.
- Strong understanding of data modeling, pipeline dependencies, schema evolution, backfills, data validation, and production data quality.
- Experience with observability, logging, alerting, and incident‐management practices for production data platforms.
- Demonstrated ability to lead complex incident resolution, perform root‐cause analysis, and convert findings into preventive improvements.
- Ability to make well‐reasoned technical decisions, identify tradeoffs, estimate work, and guide improvements across a complex platform.
- Experience mentoring engineers and collaborating effectively with Cloud / DevOps, Analytics, Security, Governance, and business stakeholders.
- Strong written and verbal English communication skills, with the ability to work directly with client stakeholders.
- Full availability to work from 9:00 AM to 6:00 PM Pacific Time and participate in an agreed on‐call rotation.
NICE TO HAVES
- Hands‐on experience with a data‐specific observability platform.
- Experience supporting Tableau Cloud administration, data‐source connectivity, extracts, scheduled refreshes, or production dashboard dependencies.
- Familiarity with Snowflake cost optimization, audit logging, tasks, stored procedures, and environment rationalization.
- Experience migrating legacy ingestion or orchestration patterns such as Boomi or AWS Data Pipeline to modern managed or Kubernetes‐based solutions.
- Experience with Terraform, CI/CD pipelines, and Infrastructure as Code practices supporting data platforms.
- Experience with service‐management and change‐control tools such as Freshservice and Jira.
- Familiarity with HIPAA, GDPR, FDA‐related controls, least‐privilege access, separation of duties, and audit‐ready operational practices.
What You Will Do
- Provide senior technical ownership for the Data Platform service tower during the LatAm coverage window, including day‐to‐day operations, complex troubleshooting, and L2/L3 escalation.
- Operate and improve Snowflake production and non‐production environments, including warehouse configuration and sizing, performance and consumption monitoring, object lifecycle, environment hygiene, and support for production changes.
- Administer data access within established controls, including users, roles, service accounts, secrets, and credential rotation, while maintaining least‐privilege and audit‐ready practices.
- Operate and improve data ingestion across Fivetran, HVR where applicable, and custom pipelines, including connector configuration, scheduling, source onboarding, schema‐change coordination, failure recovery, backfills, and dependency management.
- Design, build, and maintain reliable pipelines and dbt models across RAW, CURATED, and CONSUMPTION layers, with appropriate testing, documentation, lineage, version control, and CI/CD practices.
- Support AWS S3 data‐lake operations, including raw and landing‐zone workflows, lifecycle and retention controls, access patterns, logging, ingestion failures, and coordination with downstream Snowflake workloads.
- Support Argo Workflows and Kubernetes‐hosted data workloads in close coordination with the Cloud / DevOps team, including scheduling, troubleshooting, deployment, recovery, and capacity dependencies.
- Define and improve data quality and observability standards, including freshness, zero‐row, row‐count growth, null, duplicate, schema‐drift, and referential‐integrity checks.
- Expand end‐to‐end monitoring and lineage using tools such as SYNQ, dbt, Snowflake audit data, Splunk, and the agreed alerting stack, linking actionable alerts to evidence and runbooks.
- Lead or support major data incidents, root‐cause analysis, post‐incident reviews, and preventive actions across ingestion, orchestration, Snowflake, and downstream Tableau dependencies.
- Support Tableau Cloud operations where upstream data, connectivity, permissions, extracts, or refresh failures require Data Platform investigation.
- Identify and deliver standardization, automation, reliability, performance, and cost improvements, including migration of suitable legacy or custom extraction patterns toward agreed golden paths.
- Execute work through controlled incident, request, access, change, and release processes using established service‐management workflows.
- Create and maintain runbooks, operating procedures, architecture context, ownership information, recovery procedures, and knowledge‐transfer materials.
- Mentor Middle‐level engineers, review technical work, improve team practices, and ensure effective handoffs across the distributed service team.
- Participate in the Data Platform on‐call rotation for critical incidents outside staffed service hours.
PERKS AND BENEFITS
-
Professional growth
: Mentorship, TechTalks, and personalized growth roadmaps.
-
Competitive compensation
: USD‐based pay with education, fitness, and team activity budgets.
-
Exciting projects
: Modern solutions with Fortune 500 and top product companies.
-
Flextime
: Adaptable schedule with remote and office options.
#J-*****-Ljbffr

📌 Senior Data Engineer — Remote Pipelines, Bigquery & Spark (Buenos Aires)
🏢 1302 Argentina Delivery Center
📍 Buenos Aires