What You’ll Need
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Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
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7+ years of experience in data engineering, platform management, or similar roles, including 3+ years in a leadership position.
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Expertise in cloud-based data platforms (AWS, GCP, Azure) and big data technologies (e.g., Spark, Kafka, Databricks, Snowflake, Redshift).
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Hands-on experience designing data pipelines, ETL frameworks, and scalable data infrastructure.
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Strong understanding of data governance, security, and compliance best practices.
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Ability to communicate technical concepts effectively to non-technical stakeholders.
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Strong leadership and team-building skills with a track record of managing high-performing data engineering teams.
About the Role
We are seeking an experienced Senior Manager, Data Platform to drive our data infrastructure and analytics initiatives across the company. As a key leader within the data organization, you will be responsible for designing, implementing, and scaling data engineering strategies that enhance decision-making, operational efficiency, and business intelligence capabilities.
This role requires a deep understanding of data engineering, data management, governance, and platform scalability to enable a seamless, self-service data experience for teams across the company.
What You’ll Do
Leadership and Strategy:
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Develop and execute a 12–18-month strategy for analytics and data platform evolution, aligned with organizational objectives.
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Provide technical and strategic direction to a cross-functional team of data engineers and data platform specialists.
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Work closely with senior leadership and business stakeholders to identify opportunities for data-driven decision-making and operational improvements.
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Drive adoption of best-in-class data platform solutions that balance scalability, security, and usability.
Data Engineering & Platform Development:
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Lead the design and implementation of scalable data pipelines, ETL processes, and data warehousing solutions to ensure data accuracy, integrity, and availability.
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Evaluate and integrate cutting-edge data technologies to improve processing efficiency, storage, and accessibility.
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Build self-service analytics and BI tools to emp