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The ideal candidate must thrive on working in a fast-paced environment and demonstrate
the following:
Experience with various software development tools and other related methodologies.
Technical knowledge and experience in analytics tool and applications of data pipelines
in a multi-cloud environment.
Experience with CI/CD processes as they pertain to analytics tools.
Experience working with analytics and machine learning teams, supporting them with
secure delivery of data to perform their jobs.
Experience in defining and implementing data governance, data integration, data
privacy and data integrity policies.
Expertise in architecting cloud-native data warehouses, data pipelines, data
transformation, data models, analytics and reporting platforms.
Experience in Snowflake, dbt, Power BI, ML/AI modeling is highly preferred.
Responsibilities:
1) Design and implement data pipeline in a multi-cloud environment.
2) Create secure interfaces both internally and externally to support analytics and machine
learning.
3) Guide developers on CI/CD processes as they pertain to analytics software.
4) Participate in technical discussion, product demonstrations and provide guidance on
data pipeline subject matter expertise on compliance to business needs and technical
requirements.
5) Interact with stakeholders to ensure design, integration, quality, and deployment
expectations are being met, exceeded or non-compliance.
6) Work closely with technical teams to ensure solutions are well-architected and can
be successfully delivered.
7) Coordinate and lead internal solution design review processes.
8) Act as a technical liaison with third-party vendors to understand integration
requirements and implement custom solutions.
9) Learning and understanding of new and cutting-edge technologies for utilization
within product development and lifecycles.
10) Define and implement technical roadmap and strategies for migrating on-prem data
platforms to cloud.
11) Architect secure and scalable data analytics platform including data integrations,
data models, data transformations, B2B data shares, and user interface.