Senior Data Engineer & Analyst - Python, Google Cloud Platform
Strider
Software Engineering, IT, Data Science
Brazil · Mexico · Colombia · Argentina · El Salvador · Peru · Dominican Republic · Paraguay · Puerto Rico · Ecuador · Chile · Costa Rica · Guatemala · Bolivia · Venezuela · Nicaragua · Panama · Honduras · Uruguay · Cuba · Remote
Posted on Dec 16, 2025
Requirements
Must-haves
- 6+ years of data engineering experience
- 2+ years of Google Cloud Platform experience (BigQuery, Cloud Composer, Cloud Storage, Dataflow, DataStream)
- Experience with programming languages and frameworks, including SQL and Python
- Proficiency with workflow orchestration tools (Airflow, Cloud Composer)
- Experience with real-time and streaming data technologies (Pub/Sub, Kafka, Spark)
- Experience with building, versioning, and deploying production-grade data pipelines
- Ability to optimize queries and data models for large-scale analytical workloads
- Deep knowledge of data pipeline performance tuning and reliability practices
- Deep understanding of data modeling, semantic layers, and analytics enablement
- Ability to work in agile environments with iterative delivery and cross-functional teams
- Strong communication skills in both spoken and written English
- Bachelor's Degree in Computer Engineering, Computer Science, or equivalent
Nice-to-haves
- Startup experience
What you will work on
- Lead data engineering and analytics initiatives with a focus on data engineering and analytics delivery
- Design and evolve scalable data platforms and cloud-based data architectures
- Build, deploy, and maintain batch and streaming data pipelines across cloud environments
- Apply business logic to semantic data models to enable self-service analytics and reporting
- Optimize data pipelines for performance, scalability, reliability, and cost efficiency
- Implement and maintain CI/CD workflows for automated deployment of data pipelines and data products
- Define, monitor, and improve data quality, data consistency, and data reliability standards
- Capture and maintain data lineage, metadata, and documentation to support governance and transparency
- Develop and maintain RESTful APIs to expose curated datasets and data services
- Troubleshoot data pipeline failures and perform root-cause analysis with long-term remediation
- Collaborate with business stakeholders, analytics, IT, and data science teams to translate requirements into data solutions
- Mentor junior engineers through technical guidance, code reviews, and best practices
- Ensure compliance with security, privacy, and organizational standards across data workflows