:DataOps Engineer

Visa::USC&GC&H4EAD

We are seeking a highly skilled DataOps Engineer to help implement automation that drives the technical and business processes associated with cloud-based data platform. This would include coordinating with the Business Technology team, implementing the CI/CD for our data workflows, and helping to establish critical platform integrations into key governance and quality tools as well as downstream systems. The ideal candidate will have a strong understanding of DataOps principles, experience in teams that manage data as a product and leverage modern data tools (Kafka, Databricks, Snowflake), and a passion for automation and efficiency. This role will be instrumental in building and scaling our data platform to support data-driven decision-making across the organization.

Responsibilities:

•Hands-on implementation of automated workflows and processes for the Enterprise Data & Analytics team, ensuring performance and alignment to architectural guidelines.
•Implement and maintain DataOps CI/CD pipelines for rapid, reliable infrastructure and data product deployment, encompassing automated environment provisioning and management, testing, and linting stages.
•Develop and deploy sophisticated data pipeline automation and orchestration solutions for efficient and reliable data workflows.
•Implement and optimize monitoring and alerting systems to proactively identify and resolve issues.
•Collaborate across the organization.
•Implement DataOps best practices through automated implementation of tooling (Snowflake, dbt, Atlan, Acceldata, Airflow, and Git).
•Measure adoption and look for continuous improvement opportunities related to technology, process, and skills.
•Drive and, to the extent possible, automate the creation of detailed documentation for implemented data pipelines and operational procedures.
•Continuously tuned solutions for optimal performance.

Basic Qualifications:

•Builds and supports data workflows and analytics, focuses on data availability, quality and resiliency.
•Experience in the DataOps, DevOps, and/or Data Engineering space.
•Proven experience (3-5+ years) with core data platforms and orchestration tools such as Kafka, Databricks, Snowflake, and GitHub Actions.
•Deep practical understanding and application of DataOps principles and methodologies.
•High level understanding of data modeling, ETL/ELT processes, and data warehousing best practices.
•Hands-on experience implementing and maintaining robust CI/CD pipelines for data platforms and products.