Software Engineering LMTS

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About Salesforce

We're Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too - driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good - you've come to the right place.

Software Engineering SMTS or LMTS

Office hybrid in our San Francisco, CA office

Salesforce is embarking on our own Digital Transformation to deliver customer success for our customers and accelerate our growth. A key pillar of this transformation is building a strong data foundation to support all of our core marketing needs through intelligent data sets as a service.

We're looking for an experienced and dedicated data engineering lead who would deliver Salesforce Marketing's data foundation and automated datasets. This lead will work closely with product management, data science, data visualization, and analyst teams to support them by building data architecture and data pipelines using Google Cloud Platform(GCP), who would consume this data for producing business driven insights and AI solutions.

The right candidate will have strong experience with data infrastructure, data architecture, ETL, SQL, automation, real time data pipeline architecture, data frameworks and processes to rapidly integrate disconnected and disparate data sources into automated datasets for analysts consumption. The candidate will also have proven track record working with enterprise metrics, strong operational skills to drive efficiency and speed, expertise building repeatable data engineering processes, strong project management skills, and a vision for how to deliver data products. Experience with marketing and sales data sets is a significant advantage.

Responsibilities:

• Design and Implement of data pipelines, both batch and real time, that produces reliable data for various data consumption use cases.
• Help manage Marketing data platforms which includes the Google Cloud stack, Amazon Web services, and traditional data warehouses such as Oracle/Snowflake.
• Architect, Design and Implement real time engineering solutions on Salesforce Data Cloud.
• Manage all aspects of dataset design, creation, and curation; including the frameworks to derive metrics to deliver data products for KPI's, visualization, data science, analyst and stakeholder teams
• Build and own the automation and monitoring frameworks that showcase reliable, accurate, easy-to-understand metrics and operational KPIs to stakeholders for data pipeline quality and performance.
• Drive design, building, and launching of new data models and data pipelines in production systems
• Be the subject matter expert for data, pipeline design, and other related data cloud features and technology.
• Proactively identify reliability & data quality problems and drive triaging and remediation process
• Must have good experience in creating Workflows & scheduling the pipelines.
• 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.
• Understanding of data governance practices such as metadata management, data lineage, and data glossaries a significant advantage.
• Foster strong collaboration between globally distributed team members
• Harness operational excellence & continuous improvement with a can do attitude.

Qualification and Skills:

• A passion for data is essential - this is what we do. We are looking for people who are excited about different and unique data sets, and all the ways that they could be used in order to improve user experience.
• 13+ years total experience and 8+ years of relevant experience within big data/data warehousing domain. Proven track record of leading end to end data engineering solutions
• Solid understanding of RDBMS concepts, data structures and distributed data processing patterns.
• Strong hands on experience with building data pipelines and orchestration through components like AWS Lambdas, Airflow etc.
• Expertise in Advanced SQL & Python language is must Experience with Cloud technologies like AWS and GCP
• Experience with Salesforce Data Cloud
• Experience with Salesforce products and data model
• Experience with building/implementing DevOps methodologies
• Deep hands-on experience in complex event driven architectures and stream processing in a variety of technologies
• Proven track record in building products on some production-grade systems.
• Partner with Product Managers and Data Scientists to understand customer requirements and design prototypes and bring ideas to production.
• Passionate, curious, self-starter and innovate mentality.
• Experience with Sales and Marketing data is a significant advantage
• Knowledge of Agile methodologies, common scrum practices and tools
• Preference for candidates having certification or hands on experience with Salesforce Data Cloud
• A related technical degree required

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Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.