Title: AWS Data Engineer
Location: Singapore
Key Responsibilities
Design, build, and operate end-to-end data pipelines (ingestion → transformation → serving) on Databricks and/or Snowflake, following medallion/layered architecture patterns
Configure and administer workspaces/accounts — compute policies, resource sizing, environment setup, and access hierarchy — per the SDP reference architecture
Implement data governance controls: catalogue and schema design, RBAC, row/column-level security, data masking, and lineage tracking
Set up CI/CD and infrastructure-as-code for pipeline deployment and environment promotion (dev → test → prod)
Configure monitoring, telemetry, and audit logging to meet SDP's central observability and security posture requirements
Support UAT, integration testing, and parallel-run validation during migration and go-live
Produce handover documentation (runbooks, access lists, escalation procedures) for agency operations teams
Required Technical Skills — Databricks
Unity Catalog — catalogue/schema design, access control, and data lineage
Lakeflow / Delta Live Tables for pipeline orchestration; Delta Lake table format
Databricks SQL and cluster/workspace administration (compute policies, pools, cost management)
Databricks Asset Bundles (DABs) and Databricks Repos for CI/CD
PySpark / Spark SQL for large-scale data transformation
Working knowledge of Databricks system tables (audit logs, billing/usage, query history) for observability
Minimum 5 years of hands-on experience in Data Engineering, Data Platform Engineering, or related disciplines.
Minimum 3 years of hands-on experience with Databricks involving data pipeline development, platform administration, governance, and optimization.
Required Technical Skills — Common
Strong SQL and Python (PySpark or general-purpose) for data engineering
Data modeling — dimensional design, star/snowflake schemas, semantic layers
CI/CD pipelines (e.g., Azure DevOps, GitHub Actions, GitLab CI) for data engineering workflows
Infrastructure-as-code (Terraform preferred) for provisioning cloud data platform resources
Hands-on experience on at least one hyperscaler — AWS, Azure, or Google Cloud
Understanding of data security and compliance frameworks applicable to government/public-sector environments
Preferred Qualifications
Databricks Certified Data Engineer Associate/Professional
SnowPro Core, or SnowPro Advanced: Data Engineer
AWS certification (e.g. AWS Certified Data Engineer - Associate, Solutions Architect) and hands-on experience with AWS data services.
Prior experience delivering on a government or regulated-sector data platform, or exposure to compliance frameworks such as IM8, is an add-on
Experience working as part of a System Integrator (SI) delivery team alongside a platform Principal is an add-on
About Cognizant:
Cognizant (Nasdaq: CTSH) engineers modern businesses. We help our clients modernize technology, reimagine processes and transform experiences so they can stay ahead in our fast-changing world. Together, we're improving everyday life. See how at www.cognizant.com or @cognizant.
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关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
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