As a Senior Consultant – Data Platform Engineering, you will be responsible for designing, implementing, and supporting enterprise-scale data platform solutions leveraging AWS, Databricks, and Snowflake. You will play a key role in establishing cloud-native platform capabilities, defining reusable engineering patterns, enabling seamless integration across technologies, and ensuring platform reliability, security, and operational excellence.
The role requires strong hands-on technical expertise along with the ability to collaborate with architects, engineering teams, and business stakeholders to deliver scalable and resilient data platform solutions.
Key Responsibilities
Data Platform Engineering
- Design, build, and maintain scalable, secure, and high-performance data platform infrastructure on AWS and Databricks.
- Develop reusable platform services, frameworks, and automation capabilities to accelerate data product delivery.
- Support the implementation of cloud-native architectures aligned with enterprise data and platform standards.
- Contribute to platform modernization initiatives and continuous improvement programs.
Platform Services & Patterns
- Implement and manage common platform patterns and shared services, including:
- Auditing and compliance monitoring
- Error handling and logging frameworks
- Data lineage and traceability capabilities
- Metadata management
- Monitoring and observability solutions
- Security and access management controls
- Ensure consistency, standardization, and reusability across platform components.
Integration & Solution Development
- Design and implement integrations between AWS, Databricks, Snowflake, and other enterprise technologies.
- Develop secure, scalable, and efficient data movement and orchestration solutions.
- Enable interoperability across data ingestion, transformation, storage, governance, and consumption layers.
- Support API, event-driven, and batch integration patterns across the enterprise ecosystem.
Reliability, Security & Performance
- Ensure platform reliability, scalability, and operational readiness across development, test, and production environments.
- Implement monitoring, alerting, incident management, and operational support processes.
- Apply security best practices, including IAM, encryption, secrets management, and compliance controls.
- Identify and implement performance optimization opportunities across platform services and workloads.
- Support disaster recovery, resilience, and high-availability requirements.
Stakeholder Collaboration
- Work closely with Solution Architects, Data Engineers, Platform Engineers, Security teams, and Product Owners to deliver platform capabilities.
- Provide technical guidance and mentoring to junior consultants and engineering team members.
- Participate in architecture reviews, design discussions, and technology evaluations.
- Contribute to engineering standards, documentation, and operational runbooks.
Required Skills & Experience
- 7+ years of experience in Data Engineering, Cloud Engineering, or Data Platform delivery.
- Strong hands-on experience with AWS services such as S3, IAM, Lambda, Glue, CloudWatch, KMS, EventBridge, and Step Functions.
- Experience designing and administering Databricks-based data platforms.
- Good understanding of Snowflake architecture and integration patterns.
- Knowledge of Data Lake, Lakehouse, and modern cloud-native data platform architectures.
- Experience implementing data observability, lineage, auditing, and monitoring solutions.
- Hands-on experience with Infrastructure-as-Code (Terraform/CloudFormation) and CI/CD pipelines.
- Strong understanding of cloud security, governance, and operational support models.
- Experience troubleshooting and optimizing cloud platform performance and reliability.