Data Engineer, Slack

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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.

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 enhancement of an innovative data environment by leveraging industry best practices and cutting edge 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 talented team of data engineers.

• Architect, build and maintain scalable automated data pipelines ground up. Be an expert 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 structures

• Support 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 warehouse

• Experience working with Linux and debugging performance issues. Experience with the Salesforce Platform is a big plus.

• Strong background in Data Warehousing concepts and schema design

• Experience implementing and managing Python open source data tooling such as Airflow, DBT, SQLAlchemy, pandas, Jupyter

• History 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.

• Experience in building data pipelines using Spark (SparkSQL) with Airflow scheduler/executor framework or similar scheduling tools.

• Cloud services experience preferably with AWS

• Must exhibit strong communication skills, empathy, and initiative

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