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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コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
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