Senior Data Engineer & Analyst

  • Closed
  • US Company | Small ( employees)
  • LATAM (100% remote)
  • 6+ years
  • Long-term (40h)
  • Education
  • Full Remote

Required skills

  • SQL
  • Python
  • Google Cloud Platform
  • Spark
  • TypeScript

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