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Job Category

Software 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.

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Data Engineer

Office hybrid in Atlanta, GA

Growth Data Engineering team connects people and technology to transform the future of work at Salesforce. Guided by our core values of Trust, Customer Success, Equality, Innovation, and Sustainability, we deliver business outcomes that fuel growth, drive competitive advantage, and empower our employees and customers globally. We are strategic partners, advocating for the best outcomes for our customers, always innovating, and helping to shape the future of work.
We are responsible for technology strategy, customer and partner enablement, applications engineering, infrastructure, collaboration, enterprise operations, architecture, and program enablement. We are Customer Zero, the best example of Salesforce products delivered globally, at scale, sustainably.

Slack’s Data Engineering team sits alongside our centralized Analytics team, working together closely to ensure we are a data-driven company. Data Engineering is responsible for building and maintaining an infrastructure that powers: Product, Analytics, Marketing, Sales and Operations functions. Data Engineering is a foundational pillar for all of Salesforce and one of the most highly leveraged teams.

As a Data Engineer at Slack, you’ll be a critical part of the development and improvement of an innovative data environment by using industry standard processes and innovative approaches. You’ll collaborate with engineering to nail-down the data infrastructure, and with our business partners across all major functions at the organization to anticipate data needs, and proactively develop data solutions to address the toughest business problems. In short, you'll be building the foundation that allows the rest of the organization to understand our users and turn it into actionable steps to make our product even better and our business run smoother.

Our ideal candidate isn’t satisfied until a project is seen through to meaningful impact. If you love working with data and want to see your work impact the entire organization, we want to talk to you!

Role Overview:

Work alongside and support a versatile team of data engineers.Architect, build and maintain scalable automated data pipelines ground up. Be an authority of stitching and calibrating data across various data sources.Work with Salesforce’s data ingestion, data platform and product teams to understand and validate instrumentation and data flow.Develop data set processes for data modeling, mining and production.Integrate new data management technologies and software engineering tools into existing structuresSupport regular ad-hoc data querying and analysis to better understand customer behaviors.Understand, monitor, QA, translate, collaborate with business teams to ensure ongoing data quality.

Desired Skills:

3+ years experience designing, implementing and maintaining relational / data warehousing environments (custom or structured ETL, preferably working with large data environments)Experience with developing robust and tested Python applications to support the data warehouseExperience working with Linux and debugging performance issues. Experience with the Salesforce Platform is a big plus.Strong background in Data Warehousing concepts and schema designExperience implementing and managing Python open source data tooling such as Airflow, DBT, SQL Alchemy, pandas, JupyterHistory of designing, building and launching extremely efficient & reliable data pipelines to move data (both large and small amounts) throughout a Data Warehouse.Strong experience working with RDBMS & MPP databases (Redshift, PostgreSQL, Snowflake), with ability to optimize queries for high volume environments.Some experience in data streaming with Kafka, Kinesis would be a big plus.Must exhibit strong communication skills, empathy, and initiativeA related technical degree required

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