Senior IT Manager Enterprise Data Platform

Senior IT Manager Enterprise Data Platform

Requirements

• Desire to develop talent and foster outcomes through exceptional collaboration and teamwork.
• Broad cloud application and infrastructure architectural experience in a complex enterprise environment.
• Ability to translate business strategy into a vision for technology solutions and implementation that meet performance expectations and have high degree of re-use.
• Experience with real-time, micro-batch, and batch data ingest and data serving patterns.
• Hands-on experience in architecting and designing solutions leveraging cloud services; GCP certification and experience is a plus including: BigQuery, Google Cloud Storage, Google Data Flow, Google Dataflow, Cloud Composer/Airflow, CDAP, REST APIs, Cloud Pub/Sub, and Python Cloud Functions.
• Strong object-oriented programming experience using Python.
• Experience with data processing tools: Airflow, Apache Beam.
• Demonstrated expertise with infrastructure as code, preferably Terraform.
• Experience with billing and cost optimization in the cloud.
• Experience with CI/CD tools and processes, Git source code repositories, GitLab is a plus.
• Demonstrated expertise with Cloud computing, preferably GCP (GCS. BigQuery, Cloud Functions, IAM, DataFlow).
• Knowledge of monitoring, logging, debugging and tracing.
• Knowledge of data governance and how regulations can impact data storage and processing solutions.
• Experience with compute systems: Compute Engine, App Engine, and Containers on GCP.
• Knowledge of cloud computing concepts like Virtual Private Cloud (VPC), DNS, CDN, Load Balancing and Auto Scaling.
• Strong experience in performance tuning.
• Strong understanding of software engineering best practices and their application to data products.
• Experience building and implementing design and code standards and conducting code reviews.
• Excellent written and verbal communication skills to facilitate decision making and optimal planning at all levels of the organization.
• Passionate about learning the latest technology.

Responsibilities

• Leads a development team in designing, developing, testing, and deploying data ingest and data serving patterns to enable the Enterprise Data Platform use cases.
• Provides career growth and timely feedback to the development team to foster high quality deliverables and exceptional teamwork.
• Leads cloud architecture activities to create robust design and development patterns that provide high reliability and meet data latency SLAs.
• Establishes and monitors best practices for data ingest, data curation, and data serving solutions in GCP leveraging APIs, Google Pub/Sub, Google Dataflow, Python scripts, SQL, functions, and other services.
• Leads cloud architecture activities to validate robust design and development patterns that provide high reliability and meet data latency SLAs.
• Optimizes designs and processes to provide faster time-to-market of new products, elimination of redundant solutions, and enhanced data science initiatives.
• Protypes new solutions where new patterns or technologies are deemed essential.
• Advances and promotes enterprise data standards, source data quality assessment, ingest data completeness measurement, and metadata management.
• Modernizes and creates automation in our processes and capabilities set. Identifies opportunities to apply Artificial Intelligence (AI).
• Confirms data provisioning meets data security and auditing policies.
• Continuously improves team performance through the selection, design, and implementation of DataOps concepts, processes, and automation tools.
• Ensures tracking and root cause determination of cost increases associated with the cloud services related to the Enterprise Data Platform. Leads efforts to design enhancements to drive cost savings.
• Assists in defining data privacy and data security practices and helps translate into requirements for our Enterprise Data Platform.
• Partners with the Data Science team and Data Science Ops role to ensure seamless transfer of data model scores calculated in GCP are served to applications as expected.
• Advances and promotes enterprise data standards, source data quality assessments, ingest data completeness measurements, and metadata management.
• Works closely with the Senior Product Owner of the Enterprise Data Platform to understand and align on roadmap, scope, priorities, and resourcing.
• Promote Agile rituals such as daily stand-ups, internal sprint demos, release planning, roadmap reviews and sprint planning, are adhered to.

Preferred Qualifications

• GCP Professional Data Engineer certification preferred.