AWS Data Engineer

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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