goHappy ยท 22 hours ago
Sr. Data Analytics Engineer
goHappy is hiring a Data Analytics Engineer to help build the data foundation that powers trustworthy reporting, self-serve insights, and decision-making across the company. In this role, you'll be responsible for designing data architecture, developing foundational models, and partnering with various leaders to turn ambiguous questions into reliable data products.
Responsibilities
Execute the analytics engineering roadmap by identifying the highest-leverage data opportunities and delivering the models and datasets needed to support them
Design and build a single source of truth by developing foundational data models (dimensional modeling, star schemas, modular marts) that standardize business definitions and metrics
Manage a modern analytics infrastructure by implementing and using tools like dbt, Snowflake, and Git, including CI/CD patterns
Implement scalable standards for modeling, naming, testing, documentation, and dataset ownership to ensure maintainability as the organization grows
Improve trust in data by implementing data quality checks, monitoring and observability practices, and clear guidance on what is trusted
Partner cross-functionally with engineering, product, finance, and other business leaders to understand data needs and deliver solutions that drive decisions and outcomes
Build curated datasets and semantic-friendly layers that keep BI and reporting consistent and reliable
Create dashboards and analytics tools that empower stakeholders to self-serve confidently, with clear definitions and documentation
Translate ambiguous business questions into structured, scalable data solutions, and not one-off queries
Translate complex analytical findings into clear, actionable recommendations that influence product strategy
Act as the analytics engineering voice in technical decisions, ensuring solutions are practical, robust, secure, and useful
Drive cross-functional projects from discovery through delivery, influencing outcomes without formal authority
Contribute to data literacy and adoption through metrics definitions, training, and strong documentation
Collaborate with product managers during discovery to identify the right problems to solve using data
Qualification
Required
5 to 8+ years in analytics engineering, data engineering, BI, or closely related roles, with senior-level scope
Advanced proficiency in SQL and cloud data warehouses (Snowflake preferred)
Strong hands-on experience with dbt (or similar transformation frameworks), including modular project organization, plus testing and documentation practices
Proven ability to design scalable, reusable data models (dimensional modeling, star schemas, canonical metrics, shared dimensions)
Experience with BI tools (Looker, Tableau, Mode, or similar) and building datasets that support reliable reporting
Working knowledge of Python for scripting, automation, and data transformation
Comfort owning pipelines and data flows end-to-end (sources to warehouse to transformations to BI and downstream consumption)
Familiarity with Git and GitHub, code review workflows, and CI/CD practices for analytics code
Experience implementing data quality and reliability patterns (dbt tests, Great Expectations, Monte Carlo, alerting, SLAs, or similar)
Strong understanding of modern data architecture patterns and tradeoffs, with the ability to build what's needed now while planning for scale
Strong track record partnering with non-technical stakeholders, turning vague questions into clear requirements, then turning requirements into reliable data products
Excellent communication skills, including explaining data concepts to business audiences and aligning on definitions and outcomes
Strong prioritization instincts, focusing on work that unlocks the most value and reduces recurring pain
Comfortable operating in ambiguity, moving fast while maintaining trust and quality
Preferred
Experience with semantic modeling layers like LookML
Familiarity with workflow orchestration tools (Hevo, Airflow, Dagster)
Background in high-growth startup or tech environments
Knowledge of data cataloging and metadata management tools (Atlan, etc.)
Understanding of AI/ML applications and prompt engineering for LLMs
Experience with statistical analysis and experimental design
Company
goHappy
goHappy Hub is the most simple & powerful way to communicate and engage with your front-line workforce so they feel more connected, valued.
Funding
Current Stage
Early StageTotal Funding
unknownKey Investors
Pamlico CapitalGrowth Street Partners
2025-07-22Private Equity
2022-12-06Series Unknown
2020-01-01Seed
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