The Manager of Platform Engineering oversees the team responsible for designing and maintaining the data platform infrastructure, ensuring project delivery and resource allocation. They lead software deployment practices, facilitate collaboration with cross-functional teams, implement quality assurance standards, and drive continuous improvement in development processes.
Job Purpose and Impact
The Manager, Data Platform Engineering job sets goals and objectives for the achievement of operational results for the team responsible for designing, developing and maintaining data platform infrastructure to support information technology applications and services. This job oversees the delivery against project planning and prioritization, coordinates collaboration with cross functional teams, and allocates resources effectively and efficiently. The job also leads the team to implement best in class industry standards to continuously improve the development process.
Key Accountabilities
- PROJECT MANAGEMENT: Oversees the implementation and delivery of software projects, including resource allocation, to ensure they are completed on time and within scope.
- TECHNICAL GUIDANCE: Leads the team to apply internal software deployment platform, continuous integration or continuous delivery pipeline and twelve factor development methodology to automate the deployment process, ensuring smooth and reliable releases.
- QUALITY ASSURANCE: Leads rigorous testing, code reviews, and adherence to best in class industry standards to ensure the quality and performance of software applications.
- PROCESS IMPROVEMENT: Suggests continuous improvement initiatives and leads the implementation of approved standards to improve software development and deployment processes and operational excellence, applying test driven development as needed.
- COLLABORATION: Coordinates collaboration with product managers, designers and other cross functional teams to gather requirements, set priorities and deliver resolutions to meet business objectives.
- DOCUMENTATION: Leads and reviews the creation and maintenance of comprehensive documentation for software applications, deployment processes and system configurations.
- TECHNICAL SUPPORT: Leads technical support and troubleshooting for deployed applications for minimal downtime and fast resolution of issues.
- STAKEHOLDER MANAGEMENT: Maintains partnership with key internal and external stakeholders, understanding their needs and enabling effective communication to assure project alignment and success.
- TEAM MANAGEMENT: Manages team members to achieve the organization's goals, by ensuring productivity, communicating performance expectations, creating goal alignment, giving and seeking feedback, providing coaching, measuring progress and holding people accountable, supporting employee development, recognizing achievement and lessons learned, and developing enabling conditions for talent to thrive in an inclusive team culture.
- TECHNICAL EXPERTISE: Acts as technical thought leader and guides teams through implementation of ingestion, engineering, and metadata frameworks.
Qualifications
- Experience with CI/CD and other automation for cloud deployments and Familiarity with infrastructure as code
- Cloud infrastructure management and use of serverless technologies (AWS preferred)
- Creating technical documentation
- Experience with networking (firewall, routing, etc) and disaster recovery methods such as high availability and scalability
- Experience Programming knowledge in languages such as SQL, Python, Java or equivalent
- Experience with platform metadata, logs, and associated data for platform management.
- Experience with implementing data security tactics such as encryption and masking.
- Experience with transformation and modeling tools, including SQL based transformation frameworks, orchestration and quality frameworks such as dbt, Apache Nifi, Talend, AWS Glue, Airflow, Dagster, GreatExpectations, Oozie and others
- Experience with cloud native technologies such as Kubernetes and Docker
- Proven understanding of modern data architectures and concepts such as cloud services (AWS, Azure, GCP),real-time data distribution and processing (Kafka, Flink), and modern data warehouse tools sql (Snowflake,Databricks)
- Proven knowledge of Linux/Unix operating systems
Top Skills
Airflow
Apache Nifi
AWS
Aws Glue
Ci/Cd
Cloud Deployments
Dagster
Databricks
Dbt
Docker
Flink
Greatexpectations
Infrastructure As Code
Java
Kafka
Kubernetes
Linux/Unix
Oozie
Python
Snowflake
SQL
Talend
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