Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industry and business process expertise, and a global, collaborative workforce that embodies the future of work. Cognizant is a member of the NASDAQ-100, the S&P; 500, the Forbes Global 2000, and the Fortune 500 and is ranked among the top performing and fastest growing companies in the world.

Our Culture:

Your passion, integrity and experience are integral to Cognizant's success. You will join a dynamic and expanding global leader in IT and Business consultancy where you will be valued for who you are. We take pride in our partnership with our clients, so your ability to add value and provide exceptional service to our clients is fundamental to your success. In return, you will be presented with opportunities to develop your career and collaborate with talented colleagues in a supportive, diverse environment.

At Cognizant we recognize that companies that are open and welcoming to a multi-culturally diverse workforce will thrive with fresh perspectives and cooperative knowledge. Cognizant focuses on promoting & increasing gender diversity and providing a workplace which encourages great participation and an equal playing field, where merit and accomplishment are the only criteria for success.

Job Summary:

We are seeking an experienced Snowflake Data Engineer to design, build, optimize, and support scalable cloud data solutions on the Snowflake platform. The ideal candidate will have strong hands‑on expertise in data ingestion, transformation,



modelling, performance tuning, security, and production support, with proven experience implementing Snowpipe‑based pipelines. The role requires close collaboration with architects, analysts, developers, product owners, and business stakeholders to deliver secure, governed, reliable, and cost‑effective data products.

Key Responsibilities:

- Design, develop, and maintain scalable batch and near‑real‑time data pipelines on Snowflake.
- Implement automated data ingestion using Snowpipe and Snowpipe Streaming, including internal and external stages, file formats, cloud event notifications, error handling, monitoring, and replay mechanisms.
- Build robust ELT solutions using advanced SQL, Snowpark, stored procedures, user‑defined functions, streams, tasks, and dynamic tables.
- Design dimensional, normalized, and Data Vault models to support analytics, reporting, and downstream applications.
- Integrate data from databases, files, APIs, SaaS platforms, event streams, and cloud storage into Snowflake.
- Optimize SQL queries, virtual warehouses, clustering, caching, storage, and workload management to improve performance and control cost.
- Implement data quality checks, reconciliation controls, audit frameworks, metadata management, lineage, and operational monitoring.
- Configure secure data access using role‑based access control, masking policies,



row access policies, secure views, encryption, and network policies.
- Support secure data sharing, zero‑copy cloning, Time Travel, fail‑safe, replication, and disaster‑recovery requirements.
- Develop and maintain CI/CD pipelines, automated tests, deployment scripts, and environment‑management practices for Snowflake changes.
- Troubleshoot ingestion failures, data defects, performance bottlenecks, and production incidents across environments.
- Create solution designs, data mappings, technical specifications, operational runbooks, and knowledge‑transfer documentation.
- Perform code and design reviews, enforce development standards, and mentor junior engineers.
- Collaborate with cross‑functional teams to translate business requirements into scalable and maintainable data solutions.

Required Skills and Experience:

- 6–10 years of overall experience in data engineering, ETL/ELT development, data warehousing, or analytics engineering, including substantial hands‑on Snowflake experience.
- Strong understanding of Snowflake architecture, virtual warehouses, databases, schemas, micro‑partitions, stages, file formats, data sharing, zero‑copy cloning, Time Travel, and fail‑safe.
- Advanced SQL skills, including complex transformations, stored procedures, query profiling, performance tuning, and data‑quality validation.
- Hands‑on experience with Snowpipe and Snowpipe Streaming for automated, scalable data ingestion, including cloud event integration, monitoring, failure handling, and performance optimization.
- Experience developing Snowflake pipelines using streams, tasks, dynamic tables, stored procedures, user‑

📌 Snowflake Data Engineer (Sydney)
🏢 Cognizant
📍 Sydney