Role Description:

• Develop an in-depth understanding of Salesforce Data Intelligence/Machine Learning solutions and underlying architectures with primary focus on Event analytics platform.
• Collaborate and work with the Program managers, Data Analysts, Scientists & fellow engineers using the Agile development process.
• Implement batch/Streaming data pipelines leveraging Hive/Spark/Presto and Airflow frameworks that process data at scale ranging from GBs to TBs.
• Own implementation of the end-to-end data engineering components/frameworks. Independently delivers the components/frameworks with a quality mindset.

• Implement efficient and reliable data models for optimal storage and retrieval.
• Continuously look for opportunities to automate and build tools to lower operational barriers, improve clarity on problematic areas, and improve reliability.
• Quickly learn and adopt new technologies/processes.
• Contribute to expanding the Salesforce Data Culture by building new relationships, integrating new tools, participating/sharing in learning sessions.
• Self starter, continuously look for process/product improvement areas, effectively communicate and work towards the improvements.
• Advocate for open source data culture in the team.

If you are:

• 4+ years of experience
• Experienced Professional:
  • Good knowledge of data structures and algorithms
  • Good understanding of the data modeling patterns (both relational and dimensional)
  • Strong in Exploratory data analysis using SQL/Pandas and identify any data gaps and inconsistencies.
  • Expertise in big data technologies like Hadoop, Spark, Presto, Hive etc…
  • Strong coding skills in Python/Java/Scala or equivalent.
  • Project experience with version control systems and CICD such as GIT, GitFlow, Bitbucket, Jenkins etc.
• Experience working with Agile model.
• Innovative: have that unique viewpoint to solve problems that make others run and cower.
• Articulate technical concepts into easy-to-understand language for business partners.
• Good To have (Optional):
  • Good understanding of logging frameworks (processing unstructured application logs), log analytics and best practices.
  • Experience with cloud computing platforms such as AWS or GCP.
  • Knowledge of Salesforce Platform Admin/Development
  • Familiarity with Airflow or equivalent data pipeline orchestrators
  • (Basic) Understanding of Statistics & Machine Learning
  • Familiarity with Container Systems like Docker, Kubernetes etc.