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 data-driven marketing effectiveness measurement and customer targeting in B2B contexts
- Familiarity with Salesforce products and B2B customer data is advantageous
This role offers an exciting opportunity to leverage your data engineering expertise to power data and AI-driven innovation for the world's #1 CRM provider, working closely with our Data Science team to unlock transformative value for our vast global customer base through AI/ML-driven marketing initiatives.