Sr. Platform Engineer is an opportunity to lead and shape the next generation of data platforms fostering innovation and unlocking growth. The role involves close collaboration with multiple stakeholders including Product Owners Data Strategy Data Science and Machine Learning teams to develop innovative data products. The role requires ensuring platform stability responsiveness and alignment with business needs using best practices in cloud computing.
MustHave Skills:
7 years of experience developing and maintaining data platforms for: ETL/ELT data analysis compute & storage data pipelines orchestration metadata management and observability.
5 years of experience with Cloud Platforms (Azure GCP AWS) and cloudbased databases (Synapse Databricks Snowflake Redshift).
Platforms enabling data streaming (Kafka) microservices and data integration.
3 years of implementing data platforms with data mesh/fabric concepts.
5 years of Expertise in Agile methodologies (Scrum/Kanban) within DevSecOps models.
5 years of data platform experience in Consumer/Healthcare Goods companies and excellent understanding of business domains within the industry.
Strong interpersonal and communication skills.
Proven leadership in data platforms and architecture.
Qualifications: Undergraduate degree in Technology Computer Science Applied Data Sciences or related fields (advanced degree preferred).
GoodtoHave Skills:
Advanced knowledge of business domains in the industry.
Ability to define platforms tech stack to address data challenges: different granularity data gaps sophisticated matching logic multilanguage structured & unstructured; harmonization & normalization of data.
Ability to articulate technical concepts to business leaders and vice versa.
Responsibilities:
Provide leadership for data platforms collaborating with architecture teams to build nextgen capabilities.
Conduct proofs of concept and deliver secure scalable costeffective platforms.
Stay updated with emerging technologies and mentor platform engineers.
Ensure highquality reliable data platforms aimed at maximizing business value.
Lead data platform operations within a DevSecOps framework using modern technology stacks.
Partner with Business Analytics leaders to align platform development with business needs.
Drive prioritization and selection of tools and technologies for optimal scalability flexibility and performance.
Forge partnerships with Data Engineering Architecture and Data Science teams to scale data products.
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