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Lead Analytics Engineer
Newsela🇺🇸Remote$130K–$180K/yri2w ago
Summary
Lead Analytics Engineer to join Newsela's data team, responsible for applying data engineering best practices to transform, test, and document data while providing clean datasets and mentorship to team members.
Key Responsibilities: Build and maintain composable data models, optimize SQL query performance, transform raw data into business insights, create data visualizations, provide expert code reviews, and lead data infrastructure initiatives.
Skills & Tools: Mastered proficiency in SQL and Python with advanced experience in dbt, DAG tooling (Dagster/Airflow), business semantic layer tooling, data catalog tooling, and data integrity testing frameworks; strong autonomous work style and deep domain knowledge of data systems.
Qualifications: 8+ years of experience working with data in a software environment; required tech stack includes SQL, Python, relational datastores, dbt, Tableau, and experience with cloud infrastructure (AWS, GCP, Terraform).
Location: Remote - Argentina, Brazil, Mexico, Colombia, Chile, Costa Rica (contractor must be based in Mexico or Argentina)
Job Description
Seeking to hire a Contractor based out of Mexico or Argentina for Lead Analytics Engineering Data Team
- We are looking for a Lead 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.
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