EY's GDS Tax Technology team's mission is to develop, implement and integrate technology solutions that better serve our clients and engagement teams.
As a member of EY's core Tax practice, you'll develop a deep tax technical knowledge and outstanding database, data analytics and programming skills.
Ever-increasing regulations require tax departments to gather, organize and analyse more data than ever before.
Often the data necessary to satisfy these ever-increasing and complex regulations must be collected from a variety of systems and departments throughout an organization.
Effectively and efficiently handling the variety and volume of data is often extremely challenging and time consuming for a company.
EY's GDS Tax Technology team members work side-by-side with the firm's partners, clients and tax technical subject matter experts to develop and incorporate technology solutions that enhance value-add, improve efficiencies and enable our clients with disruptive and market leading tools supporting Tax.
GDS Tax Technology works closely with clients and professionals in the following areas: Federal Business Tax Services, Partnership Compliance, Corporate Compliance, Indirect Tax Services, Human Capital, and Internal Tax Services.
GDS Tax Technology provides solution architecture, application development, testing and maintenance support to the integral TAX service line both on a pro-active basis and in response to specific requests.
EY is currently seeking a Data Engineer - Senior to join our Tax Technology practice.
Key Responsibilities
Strong database programming/ backend development experience using SQL Server/Azure SQL, writing complex queries, stored procedures, views, triggers, cursors, UDFs.
Strong knowledge in data modeling and Datawarehouse concepts.
Experience on Azure Data Factory or any other ETL
Develops, maintains, and optimizes all data layer components for new and existing systems, including databases, stored procedures, ETL packages, and SQL queries
Experience on Azure data platform offerings.
Interacts with application developers from various core systems to address changes in those systems and their impact on existing SQL databases
Defines data solutions for business problems by working directly with project managers, seniors and clients
Ability to effectively communicate with other senior leaders of IT on program strategies and plans and negotiate quality solutions
Qualification & Experience Required
1-2 Year(s) with Microsoft Fabric
Python, PySpark, or Spark SQL experience
Lakehouse and Warehouse experience
Strong verbal and written communications skills
Ability to work as an individual contributor.
4+ years of experience on SQL DB/Server including building SQL Database, database designing and data modelling, SQL server experience with SSIS, Any ETL experience.
Experience on Azure Data Factory / SSIS and any other ETL tools.
Experience with Microsoft visual analytics tools (Power BI) and Analysis Services.
Nice to have
Experience with Agentic Coding & building new agents
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
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 / Affidavit employer.
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status, or other status protected by law or regulation.
Company Mission: Spartan Investment Group
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.
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
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