Senior Analytics Engineer

ABOUT DSC:

In 2011, we didn't just disrupt the entire shaving industry; we revolutionized it, shattering conventions with a viral video sensation that became the gold standard for humor in advertising. Our trailblazing direct-to-consumer model didn’t just pave new paths—it bulldozed age old industry giants, minting us as a force to be reckoned with.

Dollar Shave Club crafted not just products, but experiences. We made shaving not suck by cutting out all the unnecessary BS that's been upsold to guys for decades. We continued to make great f**king blades and also became the geniuses behind tons of dude-centric products like Ball Spray, offering solutions to problems men didn't know they needed.

Today we continue to expand our international grooming arsenal, and hold fast to the disruptive DNA and irreverent humor that catapulted us to fame. Our global expansion and presence in tens of thousands of retail stores are testaments to our commitment to make the hairy globe a little smoother.

Stop wasting time not working for us and come join the club!

ROLE SUMMARY:
We are hiring a Senior Analytics Engineer to drive the design and evolution of our reporting framework and its core components. You will play a pivotal role in our data strategy, creating and maintaining performant data models with a focus on usability, consistency, and data quality. You’ll work with both Data Engineering and business end users to make sure that data sources and key reports are accessible and discoverable, starting with the onboarding of new data sources through data modeling and report design. Help us develop intuitive reporting in Tableau that lets stakeholders get the most out of our data by leveraging DBT’s modeling capabilities with AWS’s Redshift data warehouse.
Additionally you’ll support our Data Engineering team with our data pipelines upstream of DBT, by having some Python experience to help read error logs and alerts to help pinpoint causes of issues.
We’re looking for someone who excels in maintaining data quality, thrives on tackling ambiguous challenges with creativity and adaptability, is adamant about producing quality documentation, and can work with both stakeholders and data producers.

RESPONSIBILITIES:

• Partner with business stakeholders to establish and refine key metrics, creating and maintaining data sources and dashboards that empower stakeholders to make data-informed decisions
• Establish standards for reporting in Tableau, drawing on experience to create intuitive and easy to use data visualizations appropriate for the data and business area 
• Lead the charge for making data discoverable by making documentation available and navigable for end users so they can self serve, and educate them on how to get the most out of Tableau
• Develop and optimize data models for analytical use cases using dbt, leveraging tests and best practices to ensure accurate, scalable, and high-quality datasets
• Serve as the architect for our dbt project: own and evolve the project’s architecture, design patterns, and best practices, ensuring consistency in data definitions and streamlined development
• Design and implement Tableau Cloud data and workbook security model, and partner with IT to manage access, user roles, and permissions
• Set up tests to ensure data quality and freshness, monitor daily job execution, and diagnose/fix issues within dbt flows, working with stakeholders to resolve root causes
• Support maintenance and troubleshooting of ETL/ELT pipelines upstream of dbt that ingest, transform, and load data from various sources into the data warehouse (e.g., cloud storage, databases, APIs)

REQUIREMENTS:

• 8+ years of experience within data and analytics
• 3+ years of experience working with dbt
• 3+ years of experience with Tableau, creating and managing data sources and dashboards
• 1+ year of experience administering a Tableau Server or Tableau Online installation
• Proficiency in SQL, with strong knowledge of data manipulation, data modeling and query performance optimization, and the ability to manage large data sets and databases
• Experience with modern databases and warehouses like Redshift, Snowflake, Postgres, MySQL, or Google BigQuery
• Excellent problem-solving and quantitative skills, including the ability to identify root causes and recommend solutions
• Meticulous attention to detail
• Familiarity with git workflows
• A proactive, solution-oriented mindset with a predisposition towards collaboration and communication

NICE TO HAVES:

• Strong perspective on analytics engineering development cycle, including data modeling, version control, documentation + testing, monitoring, and best pr