Data Engineer LMTS - Pricing
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Job CategorySoftware Engineering
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.
The Data and Analytics Organization is Salesforce's cornerstone for fostering growth and margins through unparalleled data insights. From robust governance to strategic execution, we support data pioneers with an unbiased approach. Our Enterprise Data Strategy builds a solid data foundation, fostering a culture of data-driven decisions. We ensure end-to-end quality through a cohesive data supply chain. By deploying and integration platform tools, we enable seamless data access and automated data management driving efficiency and growth with actionable insights. As a steadfast partner, we shape a data ecosystem that fuels innovation. Our commitment to integrity and accessibility propels informed decision-making, propelling Salesforce to new heights of excellence.
Data Strategy and Management Engineering team brings Data to life, partnering with data producers and platform engineers to empower data consumers (data scientists, data analysts and visualization engineers) who consume data for business analytics and AI augmented solutions. We do this by delivering trusted data, in an agile way and make it accessible for a variety of use cases. We pride ourselves in being data curious (one who has an intrinsic need to understand a data point). We architect, automate, and scale our data curation frameworks, services, and processes to rapidly integrate disconnected and disparate raw data into a business-relevant asset and work towards one common theme - Customer Success.
- Design efficient and scalable data pipelines for collecting, transforming, and loading data from various sources.
- Implement error handling and monitoring mechanisms to ensure data quality and pipeline reliability.
- Partner with data producers in understanding data sources, enable data contracts and define the data model that drives analytical use cases
- Optimize data storage solutions while implementing strategies for query performance, cost and scalability
- Monitor and enhance data pipelines' performance, availability and scalability, addressing bottlenecks and latency.
- Ensure data security and compliance with relevant regulations (e.g., GDPR,) implements data masking, access control and other data protection measures
- SME of the solution, able to connect work with the business impact
- Collaborate with cross-functional teams, provide technical guidance, and mentor junior engineers.
- Evaluate various technologies and platforms in open source and internal solutions. Execute proof of concept on new technology and tools to pick the best tools and solutions as needed
- B.S/M.S. in Computer Sciences or equivalent experience in big data engineering, data acquisition and integration projects.
- 5+ years experience designing, implementing and maintaining relational / data warehousing environments (custom or structured ETL, preferably working with large data environments)
- Strong background in Data Warehousing concepts and schema design.
- Strong proficiency in programming languages commonly used in data engineering, such as Python, SQL and big data technologies such as Hadoop, Spark, Kafka, and distributed computing frameworks.
- In-depth understanding of data modeling, lakehouse/data mesh technologies, proficiency in building frameworks and data pipelines. Experience in using test driven frameworks, version control, conducting efficient code reviews, deployment strategies
- Strong problem-solving skills and the ability to troubleshoot complex data-related issues with prime focus on data quality and management
- Excellent communication skills to collaborate with technical and non-technical stakeholders, laser focus on the impact, curious, team player
- A beginner and continuous improvement mindset, always seeking opportunities for automation, process enhancement, and reusable tool creation.
- Salesforce products knowledge, working with Salesforce metadata is a plus
- Experience working with Public Cloud platforms like GCP, AWS, Snowflake
- Familiar with production debugging techniques such as thread dump analysis and GC performance tuning
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