Remoto: Teletrabajo

Job Description 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. 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 1800 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 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. JPMorgan Key Responsibilities Extract, Transform and Load data from Third Parties into AWS Storage and Databases. Building and maintaining AWS Environments. Configure monitoring for cloud environments. Actively participate in Agile ceremonies and two-week sprint cycles. Collaborate with product owners and stakeholders to ensure data solutions align with business and regulatory requirements. 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 Must-Haves 4+ years of experience. Snowflake, including data modeling, datamarts, and data warehouse design. DBT for data transformations. Python, including object-oriented programming and data scripting. Airflow for pipeline orchestration. REST API integration and data ingestion. Google BigQuery querying and optimization. Secure handling of large-scale and sensitive data. Real-time data processing (e.g., from Google Sheets or APIs). Strong SQL, including highly optimized queries. Comprehensive documentation skills. Upper-intermediate English level. Preferred Qualifications Experience building and deploying Kubernetes based solutions. Experience with Jenkins and Spinnaker pipelines. Any experience with Azure cloud provider is also favorable. Any experience with ChatGPT API. Any experience with ODRL/DCAT. Any experience building Business Intelligence solutions Career context and Company culture AgileEngine is an Inc. 5000 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. We are looking for a Senior/Lead Data Engineer to build and maintain the pipelines and data models behind a centralized HR data warehouse. Working in Snowflake, DBT, Python, and Airflow, this person designs semantic layers that make HR data consumable by both BI tools and AI agents. Experience with Snowflake Cortex or MCP‑based tooling for agentic querying is a strong plus. What you will do (HR) Develop and maintain secure, efficient data pipelines using DBT, PySpark, and Python applications within a supported cloud environment for HR data sources. Build the infrastructure and tooling required for optimal extraction, transformation, and loading of data from a wide variety of sources using Python, DBT, Terraform, and AWS technologies such as Glue, EMR, and S3. Identify and implement internal process improvements, develop tests within the Data Quality Framework, monitor pipelines to maintain 99.5% uptime, and create and maintain the data models used by partner teams.



Design and build semantic views and ontology layers on top of existing dbt models (CORE → SEMANTIC → METRICS) so HR data is consumable by both BI tools and AI agents/LLMs. Develop and deploy AI agents (e.g., via Snowflake Cortex Analyst/Cortex Search) for HR COE use cases — including PE, iCIMS, LMS, and Sales/CS Worker agents — enabling natural‑language querying over certified HRDM data. Configure and maintain MCP (Model Context Protocol) connections between Snowflake and internal AI tooling to securely expose HR data to conversational and agentic interfaces. What you will do (ETL replacement) Document current ingestion logic inside the legacy tool, including sources, endpoints, schemas, and transformation logic. Build the ETL pipeline to replace the legacy system, handling ingestion from the Amazon API, other DSP platforms, and related digital data sources. Evaluate and decide between off‑the‑shelf solutions (e.g., Fivetran) and owned ETL systems alongside the Infrastructure Lead. Design the pipeline as a standalone, owned system to power client‑facing dashboards. Provide flexible engineering support for application and backend work within the AWS environment when directed. Coordinate with data science teams to ensure ingestion output aligns with the attribution and scoring logic of downstream models. Work seamlessly within the existing AWS environment (ECS, S3, RDS) rather than standing up parallel infrastructure. What you will do (Cost Attribution) Develop and implement tooling and datasets that drive telemetry‑driven cost attribution and performance‑informed financial modeling, enabling product, engineering, analyst, and finance stakeholders to make faster, data‑driven decisions and trust the data. Build and maintain data pipelines and tooling that provide cost transparency, surface optimization opportunities, and support committed use discount modeling and management. Relocation Relocation may be considered. International Considerations Expatriate assignments will not be considered. Visa and Sponsorship 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. Equal Opportunity Chevron Corporation is an Equal Opportunity / Aff… 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: Versátil schedule with remote and office options. Miscellaneous LangChain. LangGraph. AWS. #J-18808-Ljbffr

📌 Senior Data Engineer - Marketing Data & Bigquery (Remote) (Quilmes)
🏢 BforeAI
📍 Quilmes