Senior Product Data Analyst (Mid Shift)
Bonifacio Global City, Taguig City, Philippines
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingYou will work under the close direction of our BI Leader, who leads BI model architecture, and alongside Data Engineering, who build and run the pipelines.
Work with product managers, UX researchers and engineering leads to define metrics such as active usage, feature adoption and engagement.
From the employer’s posting
N-able is building a governed semantic layer for its business data so leaders get consistent answers, whether they ask through a dashboard or an AI analyst. The Business Intelligence Analyst, Product builds that layer for the product organization. You will work under the close direction of our BI Leader, who leads BI model architecture, and alongside Data Engineering, who build and run the pipelines. You define what Product, UX and Engineering leaders need to know across the product lifecycle, turn it into governed metrics and a semantic model in Snowflake, and prove the numbers before anyone relies on them. Dashboards are one output of that work, not the whole job. What You'll Do
What You'll Do Define the metrics. Work with product managers, UX researchers and engineering leads to define metrics such as active usage, feature adoption and engagement. Get each one signed off, document it once, and register it in the business glossary. Build the semantic layer. Build semantic views and models in Snowflake (logical tables, relationships, dimensions, measures, verified queries) over the governed data products. Put rules like "what counts as an active user" into governed columns and views rather than leaving them to individual report logic.
Tools in this posting
- SQL
- dbt
- Power BI
- Snowflake
- Tableau
Source — Tool mentions in context
- Build the semantic layer. Build semantic views and models in Snowflake (logical tables, relationships, dimensions, measures, verified queries) over the governed data products. Put rules like "what counts as an active user" into governed columns and views rather than leaving them to individual report logic. - Build and validate the data. Write and tune SQL and Snowflake objects (views, dynamic tables) that power production reporting. Reconcile results across Pendo, Salesforce and Snowflake and investigate discrepancies before stakeholders find them. - Turn feedback into measurable themes. Own NPS and Voice of the Customer reporting. Use Snowflake Cortex functions to classify, summarize and extract themes from qualitative feedback, and measure how accurate the output is.
- 3 to 5 years in BI, analytics engineering or product analytics, ideally in a SaaS or software business. - Strong SQL (CTEs, window functions, complex joins) on a cloud data warehouse, preferably Snowflake, and the habit of proving a number before publishing it. - Hands-on experience with a semantic or metrics layer (Snowflake semantic views, dbt Semantic Layer, LookML, Power BI or Tableau data models, or similar).
- Pendo, Amplitude or Mixpanel experience, including data sync into a warehouse. - Snowflake Cortex (Analyst, AI functions) or another LLM or text-to-SQL tool, and experience analyzing survey verbatims or other qualitative data. - Git and pull-request workflow for SQL and definitions.
- Snowflake Cortex (Analyst, AI functions) or another LLM or text-to-SQL tool, and experience analyzing survey verbatims or other qualitative data. - Git and pull-request workflow for SQL and definitions. - Familiarity with data governance: stewardship, certification, business glossaries.
- Strong SQL (CTEs, window functions, complex joins) on a cloud data warehouse, preferably Snowflake, and the habit of proving a number before publishing it. - Hands-on experience with a semantic or metrics layer (Snowflake semantic views, dbt Semantic Layer, LookML, Power BI or Tableau data models, or similar). - Working knowledge of dimensional modeling: grain, conformed dimensions and slowly changing dimensions.
N-able is building a governed semantic layer for its business data so leaders get consistent answers, whether they ask through a dashboard or an AI analyst. The Business Intelligence Analyst, Product builds that layer for the product organization. You will work under the close direction of our BI Leader, who leads BI model architecture, and alongside Data Engineering, who build and run the pipelines. You define what Product, UX and Engineering leaders need to know across the product lifecycle, turn it into governed metrics and a semantic model in Snowflake, and prove the numbers before anyone relies on them. Dashboards are one output of that work, not the whole job. What You'll Do
- Define the metrics. Work with product managers, UX researchers and engineering leads to define metrics such as active usage, feature adoption and engagement. Get each one signed off, document it once, and register it in the business glossary. - Build the semantic layer. Build semantic views and models in Snowflake (logical tables, relationships, dimensions, measures, verified queries) over the governed data products. Put rules like "what counts as an active user" into governed columns and views rather than leaving them to individual report logic. - Build and validate the data. Write and tune SQL and Snowflake objects (views, dynamic tables) that power production reporting. Reconcile results across Pendo, Salesforce and Snowflake and investigate discrepancies before stakeholders find them.
- Build and validate the data. Write and tune SQL and Snowflake objects (views, dynamic tables) that power production reporting. Reconcile results across Pendo, Salesforce and Snowflake and investigate discrepancies before stakeholders find them. - Turn feedback into measurable themes. Own NPS and Voice of the Customer reporting. Use Snowflake Cortex functions to classify, summarize and extract themes from qualitative feedback, and measure how accurate the output is. - Test AI answers. Support Cortex Analyst and similar tools by maintaining the question set, verified queries and expected answers used to test them. Help the business trust AI-generated answers by checking them against known results.
- Test AI answers. Support Cortex Analyst and similar tools by maintaining the question set, verified queries and expected answers used to test them. Help the business trust AI-generated answers by checking them against known results. - Deliver the reporting. Build and maintain Tableau dashboards on top of the model, and reconcile new definitions to existing reports before the older reporting is retired. - Partner and document. Work with data engineers on grain, keys and lineage (you bring meaning and rules, they bring pipelines and history). Document requirements, definitions and lineage in Confluence and track work in Jira. Raise data gaps with evidence: which question cannot be answered, and why.
- Experience with Salesforce data. - Dashboard development in Tableau or a comparable tool, enough to build, validate and reconcile reporting. Preferred
About N Able
At N-able, our mission is to protect businesses against evolving cyberthreats with an end-to-end cyber resilience platform to manage, secure, and recover.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 15, 2026 · 15 days ago
- Recorded sightings
- 18
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
At N-able, we’re not just helping businesses be secure —we’re redefining what it means to be cyber resilient. Our end-to-end platform blends AI-powered capabilities and flexible tech stacks, so customers can manage, secure, and recover with confidence. But the real power behind it all? Our people. We’re a global crew of N-ablites, who love solving complex problems, sharing knowledge, and delivering solutions that actually make a difference. If you're into meaningful work, fast growth, and a team that’s got your back, you’ll be surrounded by people who believe in what they do—and in you.
N-able is building a governed semantic layer for its business data so leaders get consistent answers, whether they ask through a dashboard or an AI analyst. The Business Intelligence Analyst, Product builds that layer for the product organization.
You will work under the close direction of our BI Leader, who leads BI model architecture, and alongside Data Engineering, who build and run the pipelines. You define what Product, UX and Engineering leaders need to know across the product lifecycle, turn it into governed metrics and a semantic model in Snowflake, and prove the numbers before anyone relies on them. Dashboards are one output of that work, not the whole job.
What You'll Do
- Define the metrics. Work with product managers, UX researchers and engineering leads to define metrics such as active usage, feature adoption and engagement. Get each one signed off, document it once, and register it in the business glossary.
- Build the semantic layer. Build semantic views and models in Snowflake (logical tables, relationships, dimensions, measures, verified queries) over the governed data products. Put rules like "what counts as an active user" into governed columns and views rather than leaving them to individual report logic.
- Build and validate the data. Write and tune SQL and Snowflake objects (views, dynamic tables) that power production reporting. Reconcile results across Pendo, Salesforce and Snowflake and investigate discrepancies before stakeholders find them.
- Turn feedback into measurable themes. Own NPS and Voice of the Customer reporting. Use Snowflake Cortex functions to classify, summarize and extract themes from qualitative feedback, and measure how accurate the output is.
- Test AI answers. Support Cortex Analyst and similar tools by maintaining the question set, verified queries and expected answers used to test them. Help the business trust AI-generated answers by checking them against known results.
- Deliver the reporting. Build and maintain Tableau dashboards on top of the model, and reconcile new definitions to existing reports before the older reporting is retired.
- Partner and document. Work with data engineers on grain, keys and lineage (you bring meaning and rules, they bring pipelines and history). Document requirements, definitions and lineage in Confluence and track work in Jira. Raise data gaps with evidence: which question cannot be answered, and why.
What You'll Bring
- 3 to 5 years in BI, analytics engineering or product analytics, ideally in a SaaS or software business.
- Strong SQL (CTEs, window functions, complex joins) on a cloud data warehouse, preferably Snowflake, and the habit of proving a number before publishing it.
- Hands-on experience with a semantic or metrics layer (Snowflake semantic views, dbt Semantic Layer, LookML, Power BI or Tableau data models, or similar).
- Working knowledge of dimensional modeling: grain, conformed dimensions and slowly changing dimensions.
- Experience with product analytics concepts such as adoption, retention, funnels and segmentation.
- Experience with Salesforce data.
- Dashboard development in Tableau or a comparable tool, enough to build, validate and reconcile reporting.
Preferred
- Pendo, Amplitude or Mixpanel experience, including data sync into a warehouse.
- Snowflake Cortex (Analyst, AI functions) or another LLM or text-to-SQL tool, and experience analyzing survey verbatims or other qualitative data.
- Git and pull-request workflow for SQL and definitions.
- Familiarity with data governance: stewardship, certification, business glossaries.
- B2B SaaS experience, ideally serving MSPs or IT management.
Purple Perks
- Medical and dental insurance
- Generous PTO and observed holidays
- 2 Paid VoluNteer Days per year
- Employee Stock Purchase Program
- Pension with company-contribution
- Monthly grab & go onsite pantry allowance
- Monthly internet allowance
- De Minimis - monthly allowance
- FuN-raising opportunities as part of our giving program
- N-ablite Learning – custom learning experience as part of our investment in you
- The Way We Work – hybrid working model of 2-3 days a week in-hub collaboration
About N-able
At N-able, our mission is to protect businesses against evolving cyberthreats with an end-to-end cyber resilience platform to manage, secure, and recover. Our scalable technology infrastructure includes AI-powered capabilities, market-leading third-party integrations, and the flexibility to employ technologies of choice—to transform workflows and deliver critical security outcomes. Our partner-first approach combines our products with experts, training, and peer-led events that empower our customers to be secure, resilient, and successful.
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- Pay
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- Location & working pattern
Bonifacio Global City, Taguig City, Philippines
- N-ablite Learning – custom learning experience as part of our investment in you - The Way We Work – hybrid working model of 2-3 days a week in-hub collaboration About N-able
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#LI-EU1 #LI-Hybrid
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