Heroku’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 Heroku and one of the most highly leveraged teams.
As the Lead Data Engineer at Heroku, you’ll lead 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!
What you’ll do:
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.
What a successful candidate will have:
5+ 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
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 etc.), with ability to optimize queries for high volume environments.
Some experience in data processing with Spark would be a big plus.
Must exhibit strong communication skills, empathy, and initiative
Apply for Senior / Lead Data Engineer You will be taken to the listing on Salesforce’s career site.