Data Engineer [Zeal]

Zeal is an AI-enabled software consultancy purpose-built for Fortune 1000 companies, and we’re now part of Livefront . We help companies navigate technology to drive business outcomes by attracting, retaining, and growing exceptional talent and empowering them to use innovative technologies and process frameworks. We’re a values-driven technology company grounded in kindness, generosity, and integrity. Our mission is to build a place where our employees love their future and where clients trust us to deliver what we promise: to improve their business through technology. Love your future. We’re looking for an outstanding Data Engineer to join our team. This role is available across our primary LATAM hub in Peru. Who you are You specialize in building data pipelines that move and transform data, and you bring basic capabilities across the full spectrum of data skills. You communicate and interact with stakeholders in a professional manner, and you take pride in pipelines that are performant, resilient, and maintainable. You are curious about new tools—including AI tools that improve your productivity. What you will be doing Gather and understand requirements for data migration and transformation. Design, build, and maintain performant, resilient, and maintainable data pipelines that meet the business requirements. Collaborate with stakeholders to ensure that designs and implementations meet requirements and project standards while fulfilling the business needs, providing feedback and proposals for alternative implementations where appropriate. Implement the required data architectures and designs using the appropriate tools and in a manner that is performant, effective, efficient, and maintainable. Shepherd the pipelines through the review and deployment process to ensure a proper implementation in production (testing, version control, and CI/CD). Monitor new and existing pipelines to ensure that they are meeting requirements and expectations. Troubleshoot and remediate new and existing pipelines to ensure continued stability and effectiveness. Document and transfer knowledge as required and appropriate within the project team. Maintain awareness and understanding of the business and technical requirements and the larger project in order to provide value beyond your specific responsibilities. Actively engage in project meetings and discussions to build context beyond your immediate tasks. Provide input and feedback to the architecture teams on the designs with an eye towards improvement. Ensure data quality, integrity, and availability with upstream and downstream systems. Contribute to data governance and best practices for data management. Why you should apply You want to work with passionate, talented people who are always looking for ways to make things better. You value a work environment where kindness, mutual trust, and egoless collaboration are paramount. You have a history of keeping promises, doing what is right, and spending energy on what matters. You enjoy the variety and growth that comes with consulting for Fortune 1000 companies across industries and technical stacks. You want to work on projects that have outsized impact and reach. You believe in sweating the details, committing to quality, and taking pride in going the extra mile. What you bring to the table We expect candidates to demonstrate a solid foundation in data engineering and a keen interest in consulting. SQL: Strong SQL skills - including an understanding of performance and parallelism. OLTP Experience: At least one year of material experience on a traditional OLTP database (Oracle, SQL Server, Postgres, etc.). MPP Experience: At least one year of material experience on a modern, MPP, data platform (Databricks, Snowflake, Azure Synapse, Redshift, BigQuery). Cloud Familiarity: Familiarity with cloud platforms including the basics of storage and security. Transformation Tools: Material experience with at least one data transformation tool (Fivetran, Informatica, DataStage, dbt, or the native tools of one of the data platforms) or the native transformation tools of the cloud providers. Data Architecture: A basic understanding of Medallion data architectures. DevOps Basics: Basic skills with orchestration (Airflow, etc.), source code control (git) and CI/CD. Communication: Effective writing and communication skills. AI Proficiency: The ability to use AI tools to improve productivity. Bonus points if you… Data Modeling: Data modeling experience on modern data platforms. Python: Python proficiency. Queuing & Events: Experience with queuing and event-driven distribution systems (Kafka, RabbitMQ, native tools of cloud platforms). Visualization: Data presentation and visualization tools (Power BI, Tableau, etc.). ELT Platforms: Specific experience with ELT on Snowflake or Databricks. Testing: Experience with testing methodologies and tools. What to expect When applying, please include a short note about yourself, a summary of your work experience, and a link to any public profiles you actively maintain (e.g., GitHub, LinkedIn). Our hiring process moves quickly and consists of several stages for candidates who capture our attention with their initial submission, sometimes including but not limited to a short preliminary phone interview, a series of video interviews, and a short take-home exercise, which you'll have up to a week to complete. Additional information We go out of our way to evaluate all employees and job applicants equitably based on merit, competence, and qualifications. We encourage candidates from all backgrounds and identities to apply, and we consider every applicant with an open mind. Don't worry, every application will be reviewed by a human.