Senior/Lead/Principal Data Engineer

Key Skills

Java Programming, Python Programming, SQL, AWS, Apache Hadoop, Scala Programming, Presto, Apache Hive, Snowflake, Docker, Kubernetes-K8s, Google Cloud Platform (GCP), SPARK Programming

Job Description

If you are currently in college/ grad school or have less than 2 years of experience - please check out FutureForce job opportunities at Salesforce:

https://www.salesforce.com/company/careers/university-recruiting/

Open to Fully Remote, Flex (1-3 days/week in the office), or Office-Based (4-5 days/week in office)

Data Intelligence (Di) is the force that propels Salesforce into the 4th Industrial Revolution informing through trusted data and artificial intelligence the path forward to be smarter in every dimension. From financial forecasting, customer health, adoption insights to the utmost trusted and curated data, the Data Intelligence team is the unbiased partner to all data trailblazers at Salesforce.

Interesting Articles about some of our work:

Lessons in Building: What Salesforce Had to Learn About Forecasting After Missing Internal Sales Goals

How AI Is Transforming Forecasting for the Better

How Salesforce CEO Marc Benioff uses artificial intelligence to end internal politics at meetings

Marc Benioff brings an A.I. machine called Einstein to his weekly staff meeting

Team Overview

The Data Science and Engineering team enables various data personas with robust and scalable frameworks, services and brings data to life. We partner with data producers and platform engineers to empower data engineers and data consumers (data scientists, data analysts and Business Intelligence engineers) with data, services and APIs for data science applications, data products and business analytics. We pride ourselves in being data curious (one who has an intrinsic need to understand a data point) and passionate about improving reliability and throughput of analytics and machine learning solutions at Salesforce. We are a globally distributed inclusive team that builds and relies on trust, constantly innovate and work towards one common theme - Customer Success.

As a Data Solutions Architect, you will be responsible for having insight into overall enterprise data ecosystem and ensuring that it meets the requirements for data needs from across the business.

Responsibilities:

• Collaborate with data, security & platform teams to outline modern data integration techniques & process using cloud technologies.
• Define how data will be collected, stored, consumed & managed.
• Drive data access methods & architect data services to improve the overall efficiency of data availability & accessibility for analytics.
• Oversee the development, management and monitoring of data pipelines.
• Ensure compliance with governing standards, data quality & protection principles.
• Provide technical guidance and oversight to help establish consistent adoption of technical design across all data onboarding initiatives.

If you are:

• Leader: Excellent solution design skills, Inspire and enable distributed teams of senior engineers.

Experienced Professional:

• Expertise in big data technologies like Hadoop, Spark, Presto, Hive, Snowflake etc...
• Strong coding skills in Python/Java/Scala or equivalent
• Good knowledge of data structures and algorithms.
• Solid understanding of engineering and data platform best practices.
• Understanding of scalability and reliability concerns for data-intensive applications
• Innovative: Can connect the dots & have that unique viewpoint to solve problems.

Collaborative & Communicative:

• Exceptional communication skills, and articulate technical concepts into easy-to-understand language for business partners.
• We love to brainstorm together!

Preferred:

• Prior experience with building end-to-end Machine Learning pipelines.
• Experience with cloud computing platforms such as AWS or GCP.
• Prior experience with docker and Kubernetes.