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vernance to strategic execution, we support data pioneers with an unbiased approach. Our Enterprise Data Strategy builds a solid data foundation, fostering a culture of data-driven decisions. We ensure end-to-end quality through a cohesive data supply chain. By deploying and integration platform tools, we enable seamless data access and automated data management driving efficiency and growth with actionable insights. As a steadfast partner, we shape a data ecosystem that fuels innovation. Our commitment to integrity and accessibility propels informed decision-making, propelling Salesforce to new heights of excellence.
Interesting Articles about some of our work and our culture:
Team Overview
Data Strategy and Management Engineering team brings Data to life, partnering with data producers and platform engineers to empower data consumers (data scientists, data analysts and visualization engineers) who consume data for business analytics and AI augmented solutions. We do this by delivering trusted data, in an agile way and make it accessible for a variety of use cases. We pride ourselves in being data curious (one who has an intrinsic need to understand a data point). We architect, automate, and scale our data curation frameworks, services, and processes to rapidly integrate disconnected and disparate raw data into a business-relevant asset and work towards one common theme - Customer Success.
Role Description:
Design, build, and maintain scalable and efficient data pipelines and ETL processes to support data-driven decision-making.
Implement data validation and monitoring processes to ensure data quality and integrity throughout the data lifecycle.
Have opinionated views on how data will be collected, stored, consumed & managed.
Ensure compliance with governing standards, data quality & protection principles.
Optimize data storage and retrieval mechanisms to enhance performance and cost-effectiveness, making data readily accessible for analytics.
Participate in code reviews and contribute to the development of coding standards and best practices to ensure high-quality data engineering solutions.
If You Are,
Experienced Data Engineer: Demonstrated experience in data engineering roles with a strong foundation in data pipeline development.
Experienced Professional:
Data Engineering Enthusiast: Passion for data engineering and a desire to grow in this field.
Collaborative & Communicative: Effective communication skills and the ability to work well within a team.
Data Advocate: Strong commitment to data quality, security, and compliance.
Preferred: Familiarity with cloud-based data platforms (https://e.g., AWS, GCP, Azure).
Minimum Requirements (Senior Data Engineer):
Accommodations
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Posting Statement
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Salesforce welcomes all.