Senior Analytics Engineer

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Digible, Inc

WebsiteLinkedInAll Job Openings

51 - 200 employees

📣 Marketing

🏠 Real Estate

☁️ SaaS

💰 $250k Seed Round on 2018-04

Marketing • Real Estate • SaaS

Digible, Inc. is a forward-thinking marketing agency that specializes in the multifamily industry. The company provides customized paid media and organic media strategies, leveraging innovative technology and data-driven analytics to enhance client visibility and reputation. Digible, Inc. offers services including SEO, social media marketing, and reputation management, with a strong focus on customer-centric, measurable programs. As a certified Google and Meta Business Partner, Digible is recognized for its commitment to transparency in pricing and reporting, fostering a culture of passion and happiness in the multifamily sector. The company is known for its transformative approach to apartment marketing, striving to redefine industry standards.

📋 Description

• Drive data warehouse strategy and performance, including modeling standards, materialization strategy, query performance, and warehouse speed and cost optimization • Own Silver- and Gold-layer modeling in dbt, including clean, documented, tested, and governed models • Consolidate redundant pre-materialized views, resolve metric drift, and correct non-additive measures at risk of bad re-aggregation • Build and govern the semantic layer as a single source of truth for metric definitions • Lead BI tooling strategy and enablement, standardizing the BI stack and enabling trustworthy self-serve analytics • Partner with stakeholders and analysts to translate business questions into durable models and metrics • Establish data best practices, governance standards, and tooling for upstream domain teams • Troubleshoot data quality and consistency issues and drive root-cause, long-term fixes • Contribute to platform evolution by optimizing, refactoring, and scaling analytics infrastructure • Report to the Director of Data and partner with Data Engineering, Product, Engineering, analysts, and business stakeholders • Deliver governed metrics, performant Silver and Gold models, and standardized BI that reduce one-off data pulls and metric disputes

🎯 Requirements

• 5-7+ years of data/analytics engineering experience, including at least 2 years in a senior capacity • Expert proficiency with SQL and data modeling tools such as dbt, Dataform, or SQLMesh • Strong command of dimensional modeling and medallion/layered architectures • Hands-on experience with at least one cloud data warehouse, such as Snowflake and/or BigQuery • Experience with data warehouse performance and cost optimization • Experience with a semantic or metrics layer, such as dbt Semantic Layer/MetricFlow, Cube, or LookML • Track record of standardizing and governing metric definitions • Proficiency with modern BI tools such as Hex, Sigma, Omni, Tableau, Looker, Metabase, or Lightdash • Working proficiency with Python for transformation, tooling, and automation • Strong proficiency with Git and version control practices • Demonstrated fluency with AI-assisted development tools • Experience working with modestly-sized, fast-paced teams • Strong communication skills and ability to partner across engineering, product, and business stakeholders • Working knowledge of iterative, value-focused technical delivery • Candidates must be located within the United States • Prolonged periods sitting at a desk and working on a computer • Must be able to lift up to 15 pounds at times • Professional references may be requested during the hiring process

🏖️ Benefits

• 4-Day Work Week (32-Hour Work Week) • US Remote — Work From Anywhere • Profit Sharing Bonus • 3 weeks PTO + Sick Leave + Bereavement • 11 paid holidays (not counting ones that fall on a Friday) • 401(k) + Match • 75% Employer-Paid Health Benefits (Medical, Dental, Vision) • Mental and Physical Wellness Reimbursement ($75/mo each) • $1,000/year travel fund (after 3+ years) • Paid Parental Leave • Dog-Friendly Office • Monthly Social Events • Weekly lunches and snacks for in-office employees