Lead Data Engineer

at Salesforce in Chicago, Illinois, United States

Job Description

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 CategorySoftware 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.

Lead Data Engineer (US Location)
We're Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Join the Marketing AI/ML Algorithms and Applications team within Salesforce's internal marketing organization. In this role, you'll have the chance to create an outsized impact on Salesforce's own marketing initiatives, helping to promote our vast product portfolio to a global customer base, including 90% of the Fortune 500.
We are seeking an expert Lead / Staff Data Engineer to orchestrate the development of scalable data platforms and pipelines that enable sophisticated customer analytics, personalization, and AI/ML-driven marketing at Salesforce. In this pivotal role, you will work closely with our Data Science team to support the full lifecycle of model development, from data exploration to production deployment.
Responsibilities:
Own the technical architecture, design, and implementation of scalable data platforms, pipelines, and feature stores to support sophisticated statistical and machine learning techniques
Develop and maintain Feature Stores to support scalable ML algorithm development and deployment, ensuring efficient and consistent access to high-quality features for predictive modeling and sophisticatedz analytics
Architect and build real-time and batch data processing systems, including ETL workflows, to integrate customer data from multiple sources, ensuring data quality and accessibility for modeling purposes
Partner with Analytics, Data Science, and Business teams to understand and meet their data needs, particularly for AI/ML-driven marketing initiatives such as propensity models, uplift models, and next-best recommender systems
Implement data infrastructure to support model deployment, monitoring, and in-production tuning processes
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 dedication to responsible and ethical use of data
Provide technical leadership and mentoring to the data engineering team, fostering a culture of innovation and continuous learning
Position Requirements:
Master's degree or equivalent experience in Computer Science, Engineering, or a related quantitative field
Shown experience in designing and developing data infrastructure and pipelines for large-scale data sets in a cloud environment
Expert 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 expertise in 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)
Familiarity with sophisticated statistical and machine learning techniques as to their data requirements
Strong experience with customer data platforms (CDPs) and customer 360 initiatives
Excellent problem-solving and partner leadership skills
Passion for enabling data-driven audience optimization and customer analytics in B2B contexts
Familiarity with sophisticated statistical and machine learning techniques as to their data requirements
Familiarity with Salesforce products and B2B customer data is... For full info follow application link.

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