Snowflakes Data Engineer

COGNIZANT TECHNOLOGY SOLUTIONS ASIA PACIFIC PTE. LTD.; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

Cognizant Technology Solutions Asia Pacific PTE. LTD. is seeking a senior data engineering professional to design, build and operate end-to-end data pipelines on Databricks and Snowflake in a regulated government-facing environment.

You will implement governance, CI/CD pipelines, and IaC to promote robust data platforms. You will collaborate with client stakeholders and architects to ensure secure, scalable, and compliant data solutions, including monitoring and go-live activities within a

Qualifications

• Minimum 5 years hands-on experience in Data Engineering, Data Platform Engineering, or related disciplines.
• Strong SQL and Python for data engineering work.
• Experience with data modeling, dimensional design, and semantic layers.

Responsibilities

• Design, build, and operate end-to-end data pipelines 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.
• Work directly with client, agency stakeholders, and Principal (Databricks/Snowflake) solution architects throughout delivery.

Skills

Data Engineering

SQL

Python

ETL

CI/CD

Cloud

Tools

Databricks

Snowflake

Snowpipe

Snowpark

RBAC

Terraform

Cloud Platforms

Job description

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
• Work directly with client, agency stakeholders, and Principal (Databricks/Snowflake) solution architects throughout delivery

Required Technical Skills — Snowflake

• Virtual warehouse sizing, scaling, and cost/performance tuning
• Snowpipe and Snowpipe Streaming for continuous ingestion
• Snowpark (Python/Scala) for in-warehouse data engineering
• Role-based access control (RBAC), secure data sharing, and object tagging for governance
• Query profiling and performance optimization (clustering keys, materialized views, caching)
• Time Travel, zero-copy cloning, and Snowflake's native data protection features
• Minimum 5 years of hands-on experience in Data Engineering, Data Platform Engineering, or related disciplines.
• Minimum 3 years of hands-on experience with Snowflakes involving data pipeline

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
• 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