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

How We Measure Seniority: From L1 to L4 Certified Expert

We don't just match keywords; we measure cognitive ability. Our Axiom Cortex™ engine evaluates every candidate against a 44-point psychometric and technical framework to precisely map their seniority and predict their success on your team. This data-driven approach allows for transparent, value-based pricing.

L1 Proficient

Guided Contributor

Contributes on component-level tasks within the Data Engineering domain. Foundational knowledge and learning agility are validated.

Evaluation Focus

Axiom Cortex™ validates core competencies via correctness, method clarity, and fluency scoring. We ensure they can reliably execute assigned tasks.

$20 /hour

$3,460/mo · $41,520/yr

± $5 USD

L2 Mid-Level

Independent Feature Owner

Independently ships features and services in the Data Engineering space, handling ambiguity with minimal supervision.

Evaluation Focus

We assess their mental model accuracy and problem-solving via composite scores and role-level normalization. They can own features end-to-end.

$30 / hour

$5,190/mo · $62,280/yr

± $5 USD

L3 Senior

Leads Complex Projects

Leads cross-component projects, raises standards, and provides mentorship within the Data Engineering discipline.

Evaluation Focus

Axiom Cortex™ measures their system design skills and architectural instinct specific to the Data Engineering domain via trait synthesis and semantic alignment scoring. They are force-multipliers.

$40 / hour

$6,920/mo · $83,040/yr

± $5 USD

L4 Expert

Org-Level Architect

Sets architecture and technical strategy for Data Engineering across teams, solving your most complex business problems.

Evaluation Focus

We validate their ability to make critical trade-offs related to the Data Engineering domain via utility-optimized decision gates and multi-objective analysis. They drive innovation at an organizational level.

$50 / hour

$8,650/mo · $103,800/yr

± $10 USD

Pricing estimates are calculated using the U.S. standard of 173 workable hours per month, which represents the realistic full-time workload after adjusting for federal holidays, paid time off (PTO), and sick leave.

Core Competencies We Validate for Data Engineering

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 for Data Engineering

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

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About TeamStation AI

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Nearshore vs. Offshore

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