SENIOR DATA
ENGINEERS

Built for Reliable Data Infrastructure.

Square Codex helps North American companies hire experienced nearshore Data Engineers from Costa Rica and Latin America who can design, build, and maintain reliable data pipelines, cloud data platforms, and analytics-ready data systems.

Our Data Engineers support data ingestion, ETL and ELT workflows, data modeling, warehouse and lakehouse architecture, workflow orchestration, data quality, governance, and scalable infrastructure for analytics, AI, and business intelligence.

WHAT OUR DATA ENGINEERS BRING

Data Pipeline Expertise

Experienced engineers who design and maintain scalable data pipelines, ETL and ELT workflows, batch processing, streaming workflows, and automated data movement across systems.

Analytics Ready Data

Professionals who understand data modeling, SQL, data warehouses, lakehouses, reporting layers, and the structure needed to make data useful for business teams.

Nearshore Alignment

Data Engineering talent from Costa Rica and Latin America working in compatible time zones with North American companies.

Reliable Data Systems

We focus on data quality, documentation, monitoring, security, governance, and maintainable data infrastructure that supports long-term growth.

DATA ENGINEERING TALENT FOR SCALABLE DATA INFRASTRUCTURE

Whether you need data pipelines, cloud data warehouses, ETL and ELT workflows, analytics engineering, data quality improvements, orchestration, migration support, or stronger data infrastructure, Square Codex can help you identify the right senior Data Engineer for your technical environment.

AI-ENABLED DATA ENGINEERS FOR MODERN DATA TEAMS

Our Data Engineers are not only experienced in data infrastructure. They also understand how modern AI-enabled workflows can improve documentation, pipeline analysis, data quality checks, troubleshooting, schema review, and analytics support.

From Claude, OpenAI, GitHub Copilot, and cloud AI services to AI-assisted SQL review, pipeline debugging, metadata analysis, documentation generation, and data quality validation, our engineers know how to use technology responsibly without replacing engineering judgment or data governance practices.

The result is a data team that can move faster, improve visibility, reduce manual work, and support analytics, AI, and business intelligence with reliable data foundations.

CORE DATA ENGINEERING CAPABILITIES FOR MODERN DATA TEAMS

Senior Data Engineers are expected to do more than move data from one place to another. They help companies design reliable data architecture, automate data workflows, improve data quality, support analytics teams, and build data infrastructure that can scale with the business.

Square Codex can help you find data talent with experience across SQL, Python, ETL and ELT processes, data warehouses, lakehouses, orchestration tools, cloud data platforms, analytics engineering, data governance, and data quality monitoring.

Data Pipeline Development

Design, build, and maintain data pipelines that move information across applications, databases, APIs, cloud platforms, and analytics systems. This can include batch processing, scheduled jobs, event-based workflows, data ingestion, transformation logic, and pipeline monitoring.

ETL and ELT Workflows

Support extraction, transformation, and loading processes that prepare data for analytics, reporting, AI workflows, and operational systems. Senior Data Engineers can help modernize legacy ETL processes, improve performance, reduce manual intervention, and make workflows easier to maintain.

Data Warehousing and Lakehouse Architecture

Build and optimize data warehouse and lakehouse environments using platforms such as Snowflake, BigQuery, Redshift, Databricks, or similar cloud data tools. This includes schema design, data modeling, storage strategy, partitioning, performance tuning, and scalable architecture.

Workflow Orchestration

Create reliable orchestration workflows using tools such as Airflow, Dagster, Prefect, or cloud-native schedulers. This helps teams automate data movement, track dependencies, manage retries, monitor failures, and keep data processes running consistently.

Analytics Engineering and Data Modeling

Prepare clean, trusted, and business-ready datasets for reporting, dashboards, product analytics, finance, operations, and leadership teams. This can include dimensional modeling, dbt workflows, SQL transformations, metrics layers, semantic models, and documentation.

Data Quality, Governance and Monitoring

Improve trust in data through validation checks, anomaly detection, monitoring, lineage, documentation, access control, privacy awareness, and governance practices. Senior Data Engineers help reduce broken reports, inconsistent metrics, and unreliable data pipelines.

How We Help You Hire Better

Understand the Data Need

We review your data sources, current pipelines, reporting needs, cloud platforms, analytics goals, data quality issues, and technical constraints before recommending talent.

Match for Technical Fit

We focus on senior Data Engineers who align with your stack, data architecture, workflow tools, cloud environment, communication needs, and delivery goals.

Support the Integration

We stay involved through onboarding and follow up to help the Data Engineer integrate successfully with your engineering, product, analytics, and business teams.