Senior Data Engineer, Analytics
Standard AI has transformed retail as we know it. With the first autonomous retail solution that works in any existing store, we enable customers to walk in, grab what they need, and walk out - without waiting in line or stopping to pay. The company’s computer vision solution is the only one that can be quickly and easily installed in retailers’ existing stores, representing a giant leap forward for retail tech that enables retailers to rapidly deliver amazing new shopping experiences to customers. Standard has launched dozens of stores alongside Circle K, Compass Group, and others and have hundreds more on the way. We’re the most well funded in our space, backed by some of Silicon Valley’s leading investors including SoftBank, CRV, Initialized, EQT, Draper Associates, and Y Combinator.
The Analytics team is structured as a centralized Analytics team at the company with embedded partnerships with Engineering, Operations, Product, and Sales teams. The team plays a critical role in informing and evangelizing data-driven decision making across all these functional areas. As a Data Engineer on the Analytics team, you will be tasked with building data pipelines that underlie our product metrics. You will be focused on building ETL pipelines, developing data schemas, and building fundamental infrastructure to enable downstream analysts and data scientists.
This is a Full Time role and can be based remotely anywhere within the US on an ongoing basis. Standard AI is a remote first company. We want our employees to have the flexibility to create work habits, locations, and schedules that best fit their lives.
What you'll do here:
- Build and maintain well-tested, up to date, documented datasets that underlie our key metrics like receipt accuracy
- Partner with stakeholder teams to ingest and process raw datasets for downstream analysts/data scientists
- Orchestrate data workflows to automate, schedule and monitor data pipelines with tools like Airflow
- Troubleshoot data quality issues and resolve broken data pipelines
- Democratize and productize our data by exposing derived data sources as APIs to other stakeholder teams
- Help to define and improve our internal standards for style, maintainability, and software engineering best practices (i.e. version control and CI/CD) for a robust data infrastructure
- Provide data engineering expertise for the rest of the Analytics Team. Lead designing the next generation of our data infrastructure
Who you are:
- You are an expert with building, maintaining and optimizing scalable data pipelines and compute, architectures, queries, and datasets. We are looking for someone who values code simplicity and performance
- You are an expert in SQL, Python and PySpark
- You have experience querying and doing transformations on large structured/unstructured datasets in SQL/Hive, Spark, Apache Flink etc.
- You are knowledgable of cloud data technologies like Snowflake and Databricks. We work with GCP services (Cloud SQL, BigQuery, Spanner)
- You have proven experience building data pipelines with orchestration tools such as AirFlow or Luigi
- You have outstanding written and verbal communication skills and comfortable presenting ideas to peers and across the company
- You are able to thrive in a remote work environment and can manage and prioritize multiple initiatives
- You have a passion for evangelizing best practices and creative problem solving. Things break, and we are looking for someone who thrives in getting to the bottom of issues
- You have a desire to learn, and improve your skills. Data is an ever evolving field, the tools of today may not be the tools of tomorrow
Why you might want to work with us:
- 100% employer-paid medical, dental and vision premiums, as well as generous contributions towards dependent premiums.
- An inclusive culture. Employee Resource Groups, DEI focused training and resources, and opportunities for community service and engagement.
- Fertility and family planning assistance provided through Maven Clinic, as well as flexible scheduling to accommodate for childcare needs and generous parental leave policies.
- Flexible Time Off to be used for vacations, sick time and/or mental health days, 12 US Company Holidays plus 2 additional Floating Holidays.
Standard provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.