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Department Overview: DnA - Operational Efficiency (Security Experience)

Data and Analytics (DnA) is a team of experts dedicated to ensuring that every decision-maker at Salesforce has timely access to the trusted data and insights they need to drive their business forward.

Our diverse global team is 300+ strong and comprises analysts, scientists, engineers, visualizers, architects, governance stewards, management, and enablement resources. Across Salesforce, we work with executives, product managers, designers, developers, user researchers, marketers, and sales strategy team members in our cloud businesses, platforms, and AI initiatives. We partner to discover new opportunities for growth and optimization, drive data-informed product strategy, and create data product experiences and actionable insights that enable our stakeholders to maximize product adoption and revenue.

The DnA Operational Efficiency team is a cornerstone of our organization, dedicated to crafting actionable insights that enhance operational efficiency and refine decision-making across all supported functions, including the Global Safety and Security portfolios. We are committed to consolidating data into a singular, reliable source to empower informed decisions, with an emphasis on thoroughly understanding the factors influencing our key metrics and their impact on our organization. The incumbent will spearhead data engineering initiatives to develop a comprehensive Security experience solution for our entire security organization.

Please note this is not a remote opportunity. It is office flexible with a minimum of 10+ times/quarter in office to collaborate with teams and /or (internal) customers.

Responsibilities:

• Design and Implement data pipelines, both batch and real time, that produces reliable data for various data consumption use cases

• Be the subject matter expert for data, pipeline design, and other related big data and programming technologies

• Proactively identify reliability & data quality problems and drive triaging and remediation process

• Partner with data producers in understanding data sources, enable data contracts and define the data model that drives analytics

• Partner with Analysts and Data Scientists on delivering reliable data that powers actionable insights

• Evaluate various technologies and platforms in open source and proprietary products. Execute proof of concept on new technology and tools to pick the best tools and solutions

• Harness operational excellence & continuous improvement with a can do demeanor

Requirements:

• 10+ years of proven experience in big data engineering

• Solid understanding of data structures and distributed data processing patterns

• Knowledge of data modeling techniques in distributed storage

• Experience in engineering data processing pipelines at scale

• Expertise in big data technologies like Hadoop, Spark, Presto, Hive, Snowflake etc..

• Knowledge of cloud data processing architectures

• Expertise in programming pipelines in Java and scripting in Python

• Experience with version control systems (Github, Stash etc..) and deployment tools

• Experience in data orchestration tools like Airflow

• Passionate, curious, creative, self-starter and approach problem with right methodology and intelligent decisions

• Laser focus on impact, balancing effort to value, and get things done

• A related technical degree required

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