Description review

Contract: Sr. Analytics Engineer - Internal Data

Newsela · Argentina, Brazil, Chile, Costa Rica · back to the listing

HR standards

44/100

poor

Title ↔ description

90/100

strong

Reads as

Data Engineer

99% confident

How others title the same work

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What the listing never says

  • 22 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
  • No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

Seeking to hire a Senior Analytical Engineer - Contractor based out of Argentina for Newsela's Internal Data Team.

• We are looking for a Senior Analytics Engineer to join our data team.

• Reporting to the Hiring Manager, you will be responsible for applying data engineering best practices to analytics code to transform, test, and document data.

• You will provide clean and organized data sets to end users.

• You will be provide expert code reviews and mentorship to other engineers in the data space

• You will be responsible for building and maintaining composable data models, as well as optimizing SQL query performance for the models you build.

• You will transform raw data into business insights, working closely with stakeholders and developing analyses to answer critical business questions.

• You will create data visualizations and help stakeholders explore and understand the data visualization tools available to them.

Why you'll love this role:

Data Modeling and Transformation

• Build new analyses and support existing ones using SQL and Python.

• Apply software engineering principles like version control and continuous integration to the analytics codebase.

• Expand our data warehouse with clean data ready for analysis.

Data Quality and Testing

• Apply advanced data testing strategies to ensure resulting datastores are aligned with expected business logic.

• Implement validation checks and automated testing procedures to manage data quality in your ETL/ELT pipelines.

Collaboration and Communication

• Work with stakeholders to define business logic and data expectations.

• Help drive a change in the usage of data by actively surfacing insights to stakeholders.

• Lead initiatives and problem definition, scoping, design, and planning.

Infrastructure and Automation

• Build tools and automation to run data infrastructure.

• Manage large-scale data migrations in relational datastores.

Why you're a great fit:

• 8+ Years experience working with data in a software environment.

• Required Skills: Mastered proficiency in SQL and Python; advanced experience managing business semantic layer tooling, data catalog tooling and data integrity testing frameworks. Experience with dbt orchestration and best practices.

• You have a track record of working autonomously and proactively, with deep domain knowledge of data systems.

• Required Tech Stack: SQL, Python, relational datastores, DAG tooling (like Dagster or Airflow), dbt and Tableau.

• Experience with cloud-based infrastructure (AWS, GCP, Terraform) and document, graph, or schema-less datastores.

Please note that given the nature of the contract, this role will not be eligible to participate in company-sponsored benefits

About Newsela:

Newsela is a leading education technology company dedicated to meaningful classroom learning for every student. We deliver integrated, AI-powered solutions designed to unlock student engagement, empower teachers, and drive meaningful learning outcomes. Our suite of products supports knowledge and skill development, writing practice, daily instruction, assessment, and data-informed decision-making across K–12 classrooms. Grounded in learning science research, Newsela’s solutions integrate content, assessment, and analytics to help educators track progress, understand student outcomes, and deliver high-impact instruction that supports every learner.

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 20 points (from 64 before penalties). Reviewed 21 Sep 2026.