Job Description:

Pickaxe is looking for a pragmatic and experienced lead data engineer/architect who enjoys helping customers organize their data in [one of Snowflake, BigQuery, Databricks] and who knows that true value of data comes when customers are actually making decisions and selections based on their queries of that information.

More specifically you will:

• As part of the data consulting team, work closely with our clients to understand their pain points and help translate those into requirements for data structure, schemas, tables, views, that provide our analyst customers with ongoing data in the most useful formats for them to take action 
• Identify the appropriate pipeline flow and work with data engineers to source and transform data and send it to the appropriate destinations for analysis, marketing needs, clean rooms, and data science modeling
• Understand and identify key user types and their specific business needs and help design or direct a schema that addresses those needs
• Assist Dev and QA and analysts with making sure what we show our clients is impeccably accurate and easily understandable and passes the common sense test
• Collaborate with the data science and development team to make adjustments to current models, presentation layers, and queries running in production

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Essentials:

• You’re proactive, entrepreneurial, and collaborative; you can work well with cross functional teams of Data Engineers, Developers, Data Scientist, Product, Analysts, and QA, and Clients.  You can spot gaps.
• You have solid time management skills, and can manage your own work stream
• You’ve got at least 5+ years of experience working with data warehouse/lakes and you understand the pros and cons of different data stores and query methods
• You understand the business practicalities of user roles, permissions, multi-tenancy, and can design an architecture with relevant affordances
• Experience as a DBA or Sr Data Engineer required (Snowflake, BigQuery, Databricks, Redshift, AWS, etc). Bonus points if you’ve overseen a multi-data source environment.
• You’ve done some analysis and understand the pain points of of business analytics and data science
• You understand the realities of data collection and have strong familiarity with tools and sources like GA4, Segment, mParticle, Billing Systems, Shopify, Amplitude, Mixpanel, Heap, Amplitude, Ad Data, etc. You won’t have to use all those systems or encounter them as sources, but you have to feel comfortable understanding how different data collection systems work and how users might need to match up data between multiple systems.

• Excellent communication skills (English).  You enjoy talking with clients.
• A sense of humor.  Life’s really short.