Analytics Engineer
for section headings, - for lists,
for prose.
We must preserve all substantive info, not invent or summarize away detail.
We need to be careful to not duplicate lines.
Let's craft.
First, About the role: combine description paragraphs up to "WHAT YOU'LL DO". Probably include the initial description about ACLU Technology Department, Analytics division, etc. We'll put in
.
Responsibilities: list bullet points from WHAT YOU'LL DO and YOUR DAY TO DAY.
Let's extract bullet points:
From WHAT YOU'LL DO:
- Reporting to the Director of Analytics Engineering, the Analytics Engineer will be part of a team focused on reliably transforming data in the ACLU’s internal systems into analysis-ready forms, scraping data from public sources, and working to improve our overall data and analysis pipeline.
- In partnership with other analytics engineers and analysts, you will use your strong technical, modeling, and analytical knowledge to assist with the data model rebuild as the ACLU migrates to a new CRM.
- The analytics engineer will work alongside data scientists, data engineers, data analysts, and business users, to enable the use of innovative data-driven methods and advanced analytics to transform the way the ACLU approaches fundraising, digital communications, and supporter engagement, as well as program work in litigation and advocacy.
From YOUR DAY TO DAY (sampling of projects):
- Design, develop, and maintain scalable data models to support reporting, business intelligence, and analytics needs using dbt.
- Collaborate with third-party vendors and our Analytics Engagement team as we prepare to migrate CRMs and re-build dbt models used for business essential reporting
- Build and orchestrate Python ETL (Extract, Transform, Load) pipelines in Dagster, to ensure the efficient flow of data from various sources into data warehouses or data lakes.
- Scrape data from public websites to support legal, organizing, and advocacy projects.
- Ensure high-quality, accurate, and timely data is available for stakeholders across departments.
- Use and help others use data warehousing and SQL best practices to keep our analytics swift and reliable
- Partner with internal departments to define and document consistent business data practices
- Collaborate with our Legal and Advocacy Analytics teams to provide data support for fast developing legal crises & issue-based campaigns
We can combine and deduplicate similar items. Keep all.
Requirements (mandatory): from WHAT YOU'LL BRING:
- Extensive experience with data warehouses and database query languages (e.g., Redshift, SQL)
- Experience building data models and writing ETL in a business setting
- Undergraduate degree in an analytical field (e.g., Economics, Statistics, Computer Science, Business) or equivalent experience
- Skilled in using a modern scripting language (e.g. Python)
- Proficiency in translating business metrics into well-scoped tasks and requirements
- Working knowledge of BI tools such as Hex, Tableau, or Looker
- Familiarity with customer relationship management (CRM) or volunteer management systems, such as Salesforce, Blackbaud, or VAN.
Preferred Qualifications:
- Demonstrated experience with a modern data stack, especially dbt for SQL data modeling
- Experience with an orchestration tool (e.g. Dagster, Airflow, Prefect)
- Knowledge of latest trends and technologies in data warehousing/data engineering
- Working knowledge of common Unix command line operations (e.g. file system operations, Docker, Git)
- Familiarity with AWS services such as S3 and Redshift
- Familiarity with voter file data
Skills: Could be overlapping; maybe we can combine Requirements and Skills? But we need separate sections only if content. Could put Requirements as mandatory, Preferred Qualifications as separate, and maybe Skills as a combined list of technical skills? However the instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have Requirements, Qualifications, Skills separate. But we have both mandatory and preferred; we could treat Requirements as mandatory, Qualifications as preferred, Skills maybe as a summary of technical skills (like Python, SQL, dbt, Dagster, etc). But we risk duplication. Better to follow typical pattern: Requirements = mandatory, Qualifications = preferred, Skills = maybe list of specific tools/technologies. However we already have those in both. To avoid duplication, we could put Requirements as the mandatory list, Qualifications as the preferred list, and Skills maybe omitted if no distinct content. But we must only include sections when posting has real specific content. If we don't have distinct Skills beyond those already covered, we could omit Skills section. However the instruction says "Prefer a few substantive sections over many thin ones." So we can omit Skills if not needed.
Thus sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay, Schedule.
Now Benefits: from WHY THE ACLU: list:
- Time away to focus on the things that matter with a generous paid time-off policy
- Focus on your well-being with comprehensive healthcare benefits (including medical, dental and vision coverage, parental leave, gender affirming care & fertility treatment)
- Plan for your retirement with 401k plan and employer match
- We support employee growth and development through annual professional development funds, internal professional development programs and workshops
Also maybe mention "We value our people..." but that's prose.
Pay: from COMPENSATION:
- The ACLU is committed to equity, transparency, and clarity in pay. Consistent with our compensation philosophy, there is a set salary for each role based on geographic work location. The annual salary for this position is $128,294 (Level G), reflecting the salary of a position based in New York, NY. Salaries are subject to a regional pay adjustment if authorization is granted to work outside of the location listed in this posting. For details on our pay structure, please visit: https://www.aclu.org/careers/ACLU_Geographic_Pay_Structure-July_2024.pdf
We should keep the URL as is.
Schedule: from hybrid role: "This is a hybrid role that has in-office requirements of two (2) days per week or eight (8) days per month."
Now About the role: include the initial paragraphs up to before WHAT YOU'LL DO. Let's capture:
"The ACLU seeks applicants for the full-time position of Analytics Engineer in the Analytics division of the Technology Department of the ACLU’s National office in New York, NY, Washington, DC, or San Francisco, CA. This is a hybrid role that has in-office requirements of two (2) days per week or eight (8) days per month. The ACLU Technology Department is a broad umbrella covering both the ACLU’s Analytics and its Product & Engineering teams, two robust and innovative divisions that power the work of the ACLU. The department provides trusted, dependable, and impactful analytics, engineering, as well as product design and management expertise for the ACLU. In partnership with experts across the ACLU, the technology team delivers best-in-class solutions, services, and innovation that advance the ACLU mission and organizational priorities. The tech team strives to ensure the ACLU leads by example in the ethical use of technology by ensuring privacy and security standards are maintained, directional insights are used to inform programming and business strategy, best-in-class products are designed to get the ACLU message out into the world and grow the ACLU supporter base, as well as to help steward high standards for algorithmic fairness, accountability, and transparency. The Analytics division includes analysts, data scientists, survey experts, social scientists, and analytics engineers that support evidence-based decision making and bring quantitative insights on our issues to the courtroom and the public. This position is part of a collective bargaining unit. It is represented by ACLU Staff United (ASU)."
Note: The schedule sentence is duplicated; we already have schedule section. Might still include in About the role but it's okay; we can keep it there as part of description but we also have separate schedule section. It's not duplicate content? It's same sentence; but we can keep it in About the role as it's part of description; but we might consider removing to avoid duplication. However instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. If we remove the schedule sentence from About the role, we lose that detail (though it's in schedule section). But we still preserve it elsewhere. It's okay to have it in both places? Might be considered duplication but not prohibited. However better to avoid duplication; we can keep schedule sentence only in schedule section and remove from About the role. But then About the role loses mention of hybrid nature; but we still have schedule section. The About the role can still describe role without schedule. It's okay.
Thus About the role paragraph will exclude the hybrid sentence.
Let's craft About the role without that sentence.
Now Responsibilities: we need to list bullet points. Use
- .
We'll combine all duties into list items.
We must ensure we don't miss any.
Let's list all distinct duties:
1. Reporting to the Director of Analytics Engineering, the Analytics Engineer will be part of a team focused on reliably transforming data in the ACLU’s internal systems into analysis-ready forms, scraping data from public sources, and working to improve our overall data and analysis pipeline.
2. In partnership with other analytics engineers and analysts, you will use your strong technical, modeling, and analytical knowledge to assist with the data model rebuild as the ACLU migrates to a new CRM.
3. The analytics engineer will work alongside data scientists, data engineers, data analysts, and business users, to enable the use of innovative data-driven methods and advanced analytics to transform the way the ACLU approaches fundraising, digital communications, and supporter engagement, as well as program work in litigation and advocacy.
4. Design, develop, and maintain scalable data models to support reporting, business intelligence, and analytics needs using dbt.
5. Collaborate with third-party vendors and our Analytics Engagement team as we prepare to migrate CRMs and re-build dbt models used for business essential reporting.
6. Build and orchestrate Python ETL (Extract, Transform, Load) pipelines in Dagster, to ensure the efficient flow of data from various sources into data warehouses or data lakes.
7. Scrape data from public websites to support legal, organizing, and advocacy projects.
8. Ensure high-quality, accurate, and timely data is available for stakeholders across departments.
9. Use and help others use data warehousing and SQL best practices to keep our analytics swift and reliable.
10. Partner with internal departments to define and document consistent business data practices.
11. Collaborate with our Legal and Advoc
for prose. We must preserve all substantive info, not invent or summarize away detail. We need to be careful to not duplicate lines. Let's craft. First, About the role: combine description paragraphs up to "WHAT YOU'LL DO". Probably include the initial description about ACLU Technology Department, Analytics division, etc. We'll put in
. Responsibilities: list bullet points from WHAT YOU'LL DO and YOUR DAY TO DAY. Let's extract bullet points: From WHAT YOU'LL DO: - Reporting to the Director of Analytics Engineering, the Analytics Engineer will be part of a team focused on reliably transforming data in the ACLU’s internal systems into analysis-ready forms, scraping data from public sources, and working to improve our overall data and analysis pipeline. - In partnership with other analytics engineers and analysts, you will use your strong technical, modeling, and analytical knowledge to assist with the data model rebuild as the ACLU migrates to a new CRM. - The analytics engineer will work alongside data scientists, data engineers, data analysts, and business users, to enable the use of innovative data-driven methods and advanced analytics to transform the way the ACLU approaches fundraising, digital communications, and supporter engagement, as well as program work in litigation and advocacy. From YOUR DAY TO DAY (sampling of projects): - Design, develop, and maintain scalable data models to support reporting, business intelligence, and analytics needs using dbt. - Collaborate with third-party vendors and our Analytics Engagement team as we prepare to migrate CRMs and re-build dbt models used for business essential reporting - Build and orchestrate Python ETL (Extract, Transform, Load) pipelines in Dagster, to ensure the efficient flow of data from various sources into data warehouses or data lakes. - Scrape data from public websites to support legal, organizing, and advocacy projects. - Ensure high-quality, accurate, and timely data is available for stakeholders across departments. - Use and help others use data warehousing and SQL best practices to keep our analytics swift and reliable - Partner with internal departments to define and document consistent business data practices - Collaborate with our Legal and Advocacy Analytics teams to provide data support for fast developing legal crises & issue-based campaigns We can combine and deduplicate similar items. Keep all. Requirements (mandatory): from WHAT YOU'LL BRING: - Extensive experience with data warehouses and database query languages (e.g., Redshift, SQL) - Experience building data models and writing ETL in a business setting - Undergraduate degree in an analytical field (e.g., Economics, Statistics, Computer Science, Business) or equivalent experience - Skilled in using a modern scripting language (e.g. Python) - Proficiency in translating business metrics into well-scoped tasks and requirements - Working knowledge of BI tools such as Hex, Tableau, or Looker - Familiarity with customer relationship management (CRM) or volunteer management systems, such as Salesforce, Blackbaud, or VAN. Preferred Qualifications: - Demonstrated experience with a modern data stack, especially dbt for SQL data modeling - Experience with an orchestration tool (e.g. Dagster, Airflow, Prefect) - Knowledge of latest trends and technologies in data warehousing/data engineering - Working knowledge of common Unix command line operations (e.g. file system operations, Docker, Git) - Familiarity with AWS services such as S3 and Redshift - Familiarity with voter file data Skills: Could be overlapping; maybe we can combine Requirements and Skills? But we need separate sections only if content. Could put Requirements as mandatory, Preferred Qualifications as separate, and maybe Skills as a combined list of technical skills? However the instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have Requirements, Qualifications, Skills separate. But we have both mandatory and preferred; we could treat Requirements as mandatory, Qualifications as preferred, Skills maybe as a summary of technical skills (like Python, SQL, dbt, Dagster, etc). But we risk duplication. Better to follow typical pattern: Requirements = mandatory, Qualifications = preferred, Skills = maybe list of specific tools/technologies. However we already have those in both. To avoid duplication, we could put Requirements as the mandatory list, Qualifications as the preferred list, and Skills maybe omitted if no distinct content. But we must only include sections when posting has real specific content. If we don't have distinct Skills beyond those already covered, we could omit Skills section. However the instruction says "Prefer a few substantive sections over many thin ones." So we can omit Skills if not needed. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay, Schedule. Now Benefits: from WHY THE ACLU: list: - Time away to focus on the things that matter with a generous paid time-off policy - Focus on your well-being with comprehensive healthcare benefits (including medical, dental and vision coverage, parental leave, gender affirming care & fertility treatment) - Plan for your retirement with 401k plan and employer match - We support employee growth and development through annual professional development funds, internal professional development programs and workshops Also maybe mention "We value our people..." but that's prose. Pay: from COMPENSATION: - The ACLU is committed to equity, transparency, and clarity in pay. Consistent with our compensation philosophy, there is a set salary for each role based on geographic work location. The annual salary for this position is $128,294 (Level G), reflecting the salary of a position based in New York, NY. Salaries are subject to a regional pay adjustment if authorization is granted to work outside of the location listed in this posting. For details on our pay structure, please visit: https://www.aclu.org/careers/ACLU_Geographic_Pay_Structure-July_2024.pdf We should keep the URL as is. Schedule: from hybrid role: "This is a hybrid role that has in-office requirements of two (2) days per week or eight (8) days per month." Now About the role: include the initial paragraphs up to before WHAT YOU'LL DO. Let's capture: "The ACLU seeks applicants for the full-time position of Analytics Engineer in the Analytics division of the Technology Department of the ACLU’s National office in New York, NY, Washington, DC, or San Francisco, CA. This is a hybrid role that has in-office requirements of two (2) days per week or eight (8) days per month. The ACLU Technology Department is a broad umbrella covering both the ACLU’s Analytics and its Product & Engineering teams, two robust and innovative divisions that power the work of the ACLU. The department provides trusted, dependable, and impactful analytics, engineering, as well as product design and management expertise for the ACLU. In partnership with experts across the ACLU, the technology team delivers best-in-class solutions, services, and innovation that advance the ACLU mission and organizational priorities. The tech team strives to ensure the ACLU leads by example in the ethical use of technology by ensuring privacy and security standards are maintained, directional insights are used to inform programming and business strategy, best-in-class products are designed to get the ACLU message out into the world and grow the ACLU supporter base, as well as to help steward high standards for algorithmic fairness, accountability, and transparency. The Analytics division includes analysts, data scientists, survey experts, social scientists, and analytics engineers that support evidence-based decision making and bring quantitative insights on our issues to the courtroom and the public. This position is part of a collective bargaining unit. It is represented by ACLU Staff United (ASU)." Note: The schedule sentence is duplicated; we already have schedule section. Might still include in About the role but it's okay; we can keep it there as part of description but we also have separate schedule section. It's not duplicate content? It's same sentence; but we can keep it in About the role as it's part of description; but we might consider removing to avoid duplication. However instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. If we remove the schedule sentence from About the role, we lose that detail (though it's in schedule section). But we still preserve it elsewhere. It's okay to have it in both places? Might be considered duplication but not prohibited. However better to avoid duplication; we can keep schedule sentence only in schedule section and remove from About the role. But then About the role loses mention of hybrid nature; but we still have schedule section. The About the role can still describe role without schedule. It's okay. Thus About the role paragraph will exclude the hybrid sentence. Let's craft About the role without that sentence. Now Responsibilities: we need to list bullet points. Use
- . We'll combine all duties into list items. We must ensure we don't miss any. Let's list all distinct duties: 1. Reporting to the Director of Analytics Engineering, the Analytics Engineer will be part of a team focused on reliably transforming data in the ACLU’s internal systems into analysis-ready forms, scraping data from public sources, and working to improve our overall data and analysis pipeline. 2. In partnership with other analytics engineers and analysts, you will use your strong technical, modeling, and analytical knowledge to assist with the data model rebuild as the ACLU migrates to a new CRM. 3. The analytics engineer will work alongside data scientists, data engineers, data analysts, and business users, to enable the use of innovative data-driven methods and advanced analytics to transform the way the ACLU approaches fundraising, digital communications, and supporter engagement, as well as program work in litigation and advocacy. 4. Design, develop, and maintain scalable data models to support reporting, business intelligence, and analytics needs using dbt. 5. Collaborate with third-party vendors and our Analytics Engagement team as we prepare to migrate CRMs and re-build dbt models used for business essential reporting. 6. Build and orchestrate Python ETL (Extract, Transform, Load) pipelines in Dagster, to ensure the efficient flow of data from various sources into data warehouses or data lakes. 7. Scrape data from public websites to support legal, organizing, and advocacy projects. 8. Ensure high-quality, accurate, and timely data is available for stakeholders across departments. 9. Use and help others use data warehousing and SQL best practices to keep our analytics swift and reliable. 10. Partner with internal departments to define and document consistent business data practices. 11. Collaborate with our Legal and Advoc