Hire Data Engineers | Nearshore Software Development

Data Engineering is the backbone of any data-driven organization. You need engineers who can build robust, scalable, and reliable data pipelines that transform raw data into actionable insights. Our vetting process, powered by Axiom Cortex™, finds experts in the modern data stack. We test their ability to build high-throughput ETL/ELT pipelines, manage data warehouses, and work with tools like Apache Spark, Kafka, and dbt.

Are your data pipelines brittle, slow, and failing silently?

The Problem

Poorly designed data pipelines are a maintenance nightmare. They are slow, prone to failure, and often fail silently, leading to corrupt or stale data in your analytics systems.

The TeamStation AI Solution

We vet for engineers who are experts in building resilient and observable data pipelines. They must demonstrate the ability to use tools like Airflow for orchestration, Spark for processing, and modern data quality frameworks to ensure data integrity.

Proof: Resilient and Observable Data Pipelines

Is your data warehouse a disorganized 'data swamp'?

The Problem

Without proper data modeling and governance, a data warehouse can quickly become a 'data swamp' where data is duplicated, inconsistent, and untrustworthy, making it useless for analytics.

The TeamStation AI Solution

Our engineers are proficient in modern data warehousing and modeling techniques. They are vetted on their ability to use tools like dbt and Snowflake to build a well-structured, documented, and trustworthy data warehouse that serves as a single source of truth.

Proof: Well-Modeled and Governed Data Warehouse

Core Competencies We Validate

ETL/ELT pipeline design and implementation

Apache Spark and distributed data processing

Data warehousing (Snowflake, BigQuery, Redshift)

Data modeling and transformation with dbt

Streaming data with Kafka or Kinesis

Our Technical Analysis

The Data Engineering evaluation focuses on building scalable and reliable data systems. Candidates are required to design an end-to-end data pipeline, from ingestion to transformation and loading into a data warehouse. A critical assessment is their ability to use Apache Spark to process a large dataset efficiently. We also test their knowledge of data warehousing concepts and their ability to use a tool like dbt to build a clean and maintainable data model. Finally, we assess their understanding of streaming data and their ability to build a real-time data pipeline with Kafka.

Related Specializations

Apache Spark dbt (Data Build Tool)Snowflake

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Stop searching, start building. We provide top-tier, vetted nearshore Data Engineering talent ready to integrate and deliver from day one.

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