Senior Data Engineer

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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.

About the company:

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.

About the team:

Join the Marketing AI/ML Algorithms and Applications team within Salesforce's Marketing organization. In this role, you'll have the opportunity to make an outsized impact on Salesforce's marketing initiatives, helping to promote our vast product portfolio to a global customer base, including 90% of the Fortune 500. By driving state-of-the-art data engineering solutions for our internal marketing platforms, you'll directly contribute to enhancing the effectiveness of Salesforce's marketing efforts. Your data engineering expertise will play a pivotal role in accelerating Salesforce's growth. This is a unique chance to apply your passion for data engineering to drive transformative business impact on a global scale, shaping the future of how Salesforce engages with potential and existing customers, and contributing to our continued innovation and industry leadership in the CRM space.

We are seeking an experienced Senior Data Engineer to develop scalable data platforms and pipelines that enable marketing effectiveness measurement and customer targeting for AI/ML-driven marketing at Salesforce. In this role, you will work closely with our Data Science team to support the full lifecycle of model development, from data exploration to production deployment for our growing portfolio of production models.

Responsibilities:

Design and implement scalable data platforms, pipelines, and features to support advanced statistical and machine learning techniques across batch and real-time processing scenarios

Contribute to development and maintenance of Feature Stores to support ML algorithm development and deployment, ensuring efficient access to high-quality features for both marketing effectiveness and customer targeting models

Build real-time and batch data processing systems, including ETL workflows, to integrate customer data from multiple sources (Snowflake, Data Cloud, etc.), ensuring data quality and accessibility for modeling purposes

Collaborate with Analytics, Data Science, and Business teams to understand and meet their data needs for marketing effectiveness models (eg, Marketing Driven Pipe, Marketing Matured ACV) and customer targeting models (eg, Product Interest, Lead Scoring, Event Intelligence, Account Propensity)

Implement data infrastructure to support model deployment, monitoring, and in-production tuning processes with output consumption through analytics platforms like Tableau

Optimize data infrastructure for performance, scalability, reliability, and cost-efficiency

Work with data stewards and custodians to ensure data quality, security, and governance, adhering to Salesforce's commitment to responsible and ethical use of data

Share technical expertise and support junior team members

Position Requirements:

5+ years experience building enterprise-scale data platforms and pipelines for large-scale data sets in a cloud environment

Strong knowledge in big data technologies such as SQL, Python, PySpark / Spark, Hive, Presto, Kafka

Strong knowledge of data modeling techniques and tools, with emphasis on database design and ETL processes

Strong experience with cloud platforms such as AWS, GCP, or Azure for data sourcing, supporting model development, and assisting with operationalization

Experience with data engineering technologies such as dbt, Airflow, data warehouses (e.g., Snowflake, Redshift) and data lakes (e.g., S3, HDFS)

Solid understanding of advanced statistical and machine learning techniques as to their data requirements

Experience with customer data platforms (CDPs) and customer 360 initiatives

Strong problem-solving and communication skills

Passion for enabling rel="noopener noreferrer">Accommodations Request Form

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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.