Senior Backend Software Engineering Contractor - Reporting
Newsela🇲🇽Remote - MexicoMX$1.2M–MX$1.8M/yri2w ago
Summary
Analytics Reporting Engineer role focused on building and maintaining data models, optimizing query performance, and serving quality data to customer reporting interfaces. Transform raw data into business insights while applying software engineering best practices to analytics infrastructure.
Key Responsibilities: Build and optimize data models using SQL and Python, implement advanced data testing strategies to ensure data quality, and maintain Python APIs for customer data serving. Collaborate with stakeholders to define business logic, manage data migrations, and automate data infrastructure processes.
Skills & Tools: Master proficiency in SQL and Python with advanced experience in business semantic layer tooling, data catalog tooling, and data integrity testing frameworks. Strong background with DBT implementation, DAG tooling (Dagster/Airflow), and cloud-based infrastructure (AWS/GCP/Terraform); Python API development experience is a plus.
Qualifications: 5+ years of experience working with data in a software environment with demonstrated ability to work autonomously and develop deep domain knowledge of data systems. Required tech stack includes SQL, Python, OLAP datastores, and DBT.
Location: Remote - Argentina, Brazil, or Mexico
Job Description
Seeking to hire a Contractor based out of Argentina or Mexico for Senior-Level Back End Engineering Services (Reporting)
Scope of Services:
- We are looking for an Analytics Reporting Engineer to join our data team.
- Reporting to the Hiring Manager, you will be responsible for applying best practices in data modeling, data transformation, data testing for serving quality data to customer reporting interfaces.
- You will be responsible for building and maintaining composable data models, optimizing SQL query performance and maintaining python APIs for serving data to customers.
- You will transform raw data into business insights, working closely with stakeholders to serve data to critical customer reporting interfaces.
Why you'll love this role:Data Modeling and Transformation
- Build new models and optimize 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 data transformation and API layers.
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:
- 5+ 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 implementation and best practices.
- Experience with Python API development is a plus, but not required.
- Experience with GCP services is preferred but not required.
- You have a track record of working autonomously, with developing a deep domain knowledge of data systems.
- Required Tech Stack: SQL, Python, OLAP datastores, DAG tooling (like Dagster or Airflow), and DBT
- 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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