Time since we first saw it
Day 213
Up longer than most. Similar jobs usually come down between day 7 and day 51.
From 1,662 similar postings that came down. Coming down is not always a hire.
Build and maintain scalable data models using tools like Snowflake and dbt
Work with Data Engineering to automate pipelines and reduce manual reporting
Develop and maintain dashboards for consistent business performance visibility
Validate data and reconcile figures across Salesforce and billing systems
Build and maintain scalable data models using modern tools (e.g., Snowflake, dbt)
Work with Data Engineering to automate data pipelines and reduce manual reporting processes
Develop and maintain dashboards that provide consistent and reliable visibility into business performance
Validate data outputs, identify inconsistencies, and support reconciliation efforts across systems (e.g., Salesforce, billing systems)
Strong SQL skills and experience working with structured and large datasets
Ability to work with global teams across time zones
Experience with modern data tools (e.g., Snowflake, dbt, Looker or similar)
Experience building and maintaining data models and dashboards
Experience implementing business logic into data transformations
Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise.
In the employer’s words · Read in context
Open 7 monthsWe first saw this posting 213 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 213
Up longer than most. Similar jobs usually come down between day 7 and day 51.
From 1,662 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Typically requires a minimum of 5 years of related experience in financial data analytics, business intelligence, or analytics engineering - Strong SQL skills and experience working with structured and large datasets - Experience with modern data tools (e.g., Snowflake, dbt, Looker or similar)
Responsibilities: Data Modeling & Transformation Build and maintain scalable data models using modern tools (e.g., Snowflake, dbt). Translate defined business logic (e.g., ARR calculations) into clean and reusable datasets. Metrics Implementation Implement and maintain standardized metrics (e.g., ARR, NRR, churn) in the data layer. Ensure consistency across dashboards and reports.
- Strong SQL skills and experience working with structured and large datasets - Experience with modern data tools (e.g., Snowflake, dbt, Looker or similar) - Experience building and maintaining data models and dashboards
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New Analytics Engineer postings at the employers we follow are down 14% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
LaunchDarkly is looking for a Data Analyst to join our Data & Analytics team in Ireland. In this role, you will focus on building and scaling reliable data models, automating reporting, and supporting global analytics delivery.
You will partner closely with the Senior Financial Analyst (Revenue & Metrics), Data Engineering, and business stakeholders to translate business logic into clean, scalable datasets. This role plays a key part in ensuring that defined metrics (e.g., ARR, NRR) are consistently implemented, automated, and delivered across the organization.
Data Modeling & Transformation
Build and maintain scalable data models using modern tools (e.g., Snowflake, dbt). Translate defined business logic (e.g., ARR calculations) into clean and reusable datasets.
Metrics Implementation
Implement and maintain standardized metrics (e.g., ARR, NRR, churn) in the data layer. Ensure consistency across dashboards and reports.
Automation & Pipeline Support
Work with Data Engineering to automate data pipelines and reduce manual reporting processes.
Dashboarding & Reporting
Develop and maintain dashboards that provide consistent and reliable visibility into business performance.
Data Quality & Validation
Validate data outputs, identify inconsistencies, and support reconciliation efforts across systems (e.g., Salesforce, billing systems).
Global Collaboration
Partner with teams across the US and EMEA to deliver timely and high-quality analytics outputs.
Typically requires a minimum of 5 years of related experience in financial data analytics, business intelligence, or analytics engineering
Strong SQL skills and experience working with structured and large datasets
Experience with modern data tools (e.g., Snowflake, dbt, Looker or similar)
Experience building and maintaining data models and dashboards
Experience implementing business logic into data transformations
Strong attention to detail and ability to ensure data accuracy
Ability to work with global teams across time zones
Clear communication skills
Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations.
The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by:
At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com.
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Ireland
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