Data Engineer
Posted 4 Mar 2026
Advertised as “Senior Data Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Contract
No salary listed for this role.
About CodeRoad
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. 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 requirements into technical reality.
Key Responsibilities
- Pipeline Development: Design and build robust ETL/ELT processes to handle large-scale data ingestion and transformation.
- Architecture Design: Lead the evolution of data warehouses, lakes, and streaming architectures to support business intelligence and analytics.
- 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
- Experience: 5+ years of dedicated data engineering experience.
- 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.
- Environment: Mandatory experience in nearshore/offshore client-facing startup cultures.