GBS Chevron Global Business Services (GBS), located in Buenos Aires (Puerto Madero), Argentina, is accepting online applications from professionals interested in Data Analyst and Data Engineering opportunities. Successful candidates will join the center, 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. 

Successful candidates will join the Data & Insights organization within a global, multifunctional service center delivering business services and technology solutions across the globe. Based on their experience, skills, and interests, candidates may be considered for opportunities focused on data analysis, data management, data modeling, data quality, data engineering, data products, analytics enablement, or a combination of these areas.

About the role

Professionals in these roles help transform business needs and data into trusted, accessible, reusable, and scalable data solutions. Depending on the position and candidate profile, responsibilities may range from understanding how business workflows map to data to designing, building, deploying, and maintaining automated data pipelines and data products.

Responsibilities may include

• Understanding business uses of data and gathering stakeholder requirements to support work processes and strategic objectives.
• Partnering with business units, digital platforms, functional teams, architects, data scientists, and delivery teams.
• Translating business workflows and requirements into data definitions, models, products, and technical solutions.
• Analyzing existing data management processes, practices, tools, and capabilities.
• Helping define future data needs and contributing to common information models.
• Identifying, acquiring, cleansing, preparing, validating, storing, and transforming data.
• Designing, developing, deploying, and maintaining scalable and reusable data pipelines and data products.
• Applying data and software engineering techniques to improve data accessibility and create business value.
• Advising teams on data integration patterns, data modeling, data architecture, and data quality.
• Assessing data-quality concerns and driving appropriate mitigation activities.
• Maintaining and sharing knowledge of data requirements, definitions, stores, creation processes, and key data types.
• Making data available to support analytics, reporting, data science, and advanced analytical models.
• Collaborating with data analysts, engineers, architects, and data scientists to scale and deploy data solutions.
• Producing and maintaining relevant documentation and supporting training and integration activities.
• Contributing to foundational tools, reusable components, technical services, and inner-source development.
• Serving as a data subject-matter expert for business and delivery teams when appropriate.

Required qualifications

• Bachelor’s degree in Information Technology, Engineering, Data Science, Computer Science, Business Analytics, or a related field, or equivalent relevant experience.
• Experience or knowledge in one or more of the following areas:
  • Data analysis and data management.
  • Data acquisition, wrangling, preparation, and validation.
  • Data movement, integration, and transformation.
  • Data modeling and information modeling.
  • Data quality, data strategy, policies, or governance.
  • Data engineering and software engineering.
  • Development of data pipelines or reusable data products.
  • Business intelligence, reporting, or analytics.
• Strong analytical and problem-solving skills.
• Ability to understand business workflows and translate business needs into data requirements or solutions.
• Strong collaboration and communication skills.
• Ability to work effectively with business and technical stakeholders.

Technical experience

Depending on the specific opportunity, relevant experience may include one or more of the following:

• SQL, including the ability to understand or develop complex queries, views, stored procedures, and tables.
• Microsoft SQL Server and SQL Server Management Studio.
• Azure Data Factory.
• Azure Databricks.
• Azure Synapse Analytics.
• DevOps practices and tools.
• Power BI.
• Python.
• Ansible.
• Big-data computing technologies.
• ETL or ELT processes.
• Data integration and analytics-processing technologies.
• Data models, data architectures, and common information models.

These requirements consolidate the Azure, SQL, Power BI, Python, Ansible, data modeling, governance, and engineering technologies identified in the two original descriptions.  

Preferred qualifications

• Experience developing automated data pipelines or reusable data products.
• Experience supporting data foundation or data-management initiatives.
• Knowledge of analytics, reporting, or advanced analytics workflows.
• Experience working with cloud-based data platforms.
• Knowledge of software engineering principles applied to data solutions.
• Experience collaborating with data scientists, data architects, business stakeholders, and delivery teams.
• Familiarity with data governance, data quality, and metadata-management practices.

Important: Candidates are not expected to have experience in every area listed. Applications are encouraged from professionals whose background is stronger in either data analysis or data engineering, as well as candidates with experience across both disciplines.

Relocation Options:

Relocation could 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.