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data

Posted Mar 4

Senior Data Engineer

at CodeRoad

Latin America, United StatesOn-site
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Responsibilities

  • Architecture Design: Lead the evolution of data warehouses, lakes, and streaming architectures to support business intelligence and analytics.

Requirements

  • This role is open to experts in various on-demand technologies (Snowflake, Databricks, Redshift, etc.), requiring a focus on data integrity and high-performance processing.
  • Your success is measured by the efficiency of data workflows, the reliability of data lakes/warehouses, and your ability to translate complex data
  • Data Tech: Proficiency with modern data stacks (e.g., Spark, Airflow, Kafka, dbt) and cloud data warehouses (Snowflake, BigQuery, or Redshift).
  • Languages: Advanced proficiency in SQL and Python or Scala. Cloud:
  • Experience building data solutions on AWS, Azure, or GCP.
  • Modeling: Strong understanding of data modeling techniques (Star Schema, Data Vault, etc.).
  • Communication: Advanced English proficiency (written and verbal) for collaboration with US-based clients.
  • experience in nearshore/offshore client-facing startup cultures. What you’ll love:

Experience

  • Experience: 5+ years of dedicated data engineering experience.

Benefits

  • Competitive Pay (USD)
  • Holidays Off & Paid Time Off
  • Health insurance assistance program

Additional details

  • CodeRoad provides end-to-end software development services, helping businesses scale with ideal infrastructure solutions.
  • From staff augmentation to dedicated IT teams and general software engineering, our nearshore technology services empower businesses to thrive in an ever-evolving digital landscape. About the Role
  • As a Senior Data Engineer, you will own the design and evolution of scalable data pipelines and architectures.
  • You will act as the primary anchor for data ingestion, transformation, and storage solutions, ensuring that mission-critical data is accessible and reliable.
  • requirements into technical reality. Key Responsibilities
  • Pipeline Development: Design and build robust ETL/ELT processes to handle large-scale data ingestion and transformation.
  • Data Quality: Implement rigorous testing and monitoring to ensure data accuracy, consistency, and security.
  • Optimization: Manage and tune database performance, ensuring low-latency access for downstream applications.
  • Team Influence: Collaborate with Data Scientists and Stakeholders to define data models and support the growth of junior engineers through technical mentorship. Requirements •
  • Opportunity to work with high-growth US-based companies and cutting-edge tech stacks.

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