Salesforce, Inc..
Data Engineer MTS
Office hybrid in San Francisco, Seattle or Indianapolis
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.
Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes to support data analytics and reporting. Collaborate with Data Scientists and Stakeholders 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. Required Skills/Experience 2-4 years related information systems experience in a data engineering, data modeling, automation and analytics A related technical degree required Deep understanding of data engineering concepts, database designs ,associated tools, system components, internal processes and architecture. . Experience in writing and maintaining complex ETL Knowledge on salesforce components like flows Experience working closely with Analytics/Data Science teams Proficiency with SQL, Bash and Python scripting Proficiency with Airflow for orchestrating complex pipelines Proficiency with API based real time ingestions Team-first mentality.Excellent interpersonal skills in order to build strong relationships that will be critical for the success in this role. Must be able to proactively communicate status and identify risks Must be results oriented and able to move forward without complete information and with minimal supervision Experience with ETL technologies (Mulesoft, Jitterbit, Informatica etc.) Experience with Marketing technology, Salesforce Data models or Data Cloud are a huge plus
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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.
Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes to support data analytics and reporting. Collaborate with Data Scientists and Stakeholders 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. Required Skills/Experience 2-4 years related information systems experience in a data engineering, data modeling, automation and analytics A related technical degree required Deep understanding of data engineering concepts, database designs ,associated tools, system components, internal processes and architecture. . Experience in writing and maintaining complex ETL Knowledge on salesforce components like flows Experience working closely with Analytics/Data Science teams Proficiency with SQL, Bash and Python scripting Proficiency with Airflow for orchestrating complex pipelines Proficiency with API based real time ingestions Team-first mentality.Excellent interpersonal skills in order to build strong relationships that will be critical for the success in this role. Must be able to proactively communicate status and identify risks Must be results oriented and able to move forward without complete information and with minimal supervision Experience with ETL technologies (Mulesoft, Jitterbit, Informatica etc.) Experience with Marketing technology, Salesforce Data models or Data Cloud are a huge plus
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