Data Engineer - Multiple levels

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Software Engineering

Job Details

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.

Data Engineer - multiple levels

Office hybrid - San Francisco, CA

In school or graduated within the last 12 months? Please visit Futureforce for opportunities.

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 to build data platforms and automated data pipelines to provide data-driven insights and recommendations to support the growth in Marketing.

We are looking for a Data engineer who has experience building data pipelines and metrics for Sales or Marketing organizations. In this role, you will work with business partners across Marketing functions to understand business needs, translate them to technical requirements, wrangle data from various systems, and design automated data pipelines to drive insights. You will work with internal technology groups to automate the data collection and definition process.

The Data Engineer will also be responsible end-to-end data management activities, including but not limited to identify fields, data lineage and integration, performing data quality checks, analysis and presenting data on Salesforce Data Cloud as platform/product.

For the Lead role, experience should include significant 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. Experienced and committed data engineering lead who would deliver Salesforce Marketing’s data foundation and automated datasets on Salesforce Data Cloud. 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.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL processes to support data analytics and reporting.

• Collaborate with Data Scientists and Analysts to understand data requirements and implement data solutions.

• Build and optimize data models and databases (relational, NoSQL) to support application development and data warehousing.

• Implement data governance best practices to ensure data quality, integrity, and security.

• Monitor and troubleshoot data pipelines and infrastructure performance issues.

• Work with cloud platforms (AWS, Azure, GCP) and Salesforce Data Cloud to manage and process large datasets.

• Support the integration of new data sources and APIs into existing data pipelines.

• Partner with Product Managers and Data Scientists to understand customer requirements and design prototypes and bring ideas to production

Required Skills/Experience

• 6+ years related information systems experience in a data engineering, data modeling, automation and analytics.

• Deep understanding of data engineering concepts, database designs, associated tools, system components, internal processes and architecture.

• Experience in writing and maintaining complex ETL (i.e. Mulesoft, Jitterbit, Informatica, etc.)

• Proven track record of leading end to end data engineering solutions.

• Hands on experience with building data pipelines and orchestration through components like AWS Lambdas, Airflow etc.

• Solid under