Data & Migration Engineer

BlueVector AI; Denver (CO); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Health, Dental, and Vision insurance

Simple IRA Retirement plan with match

Unlimited PTO

Google Certification reimbursement

Job summary

BlueVector AI in Denver, CO is seeking a mid-level Data & Migration Engineer to untangle legacy data systems and move them to Google Cloud. You will design ETL/ELT pipelines, work with client teams and internal engineers, and push data into production.

Build clean data models, optimize SQL and Python scripts, and ensure reliable migrations with quality checks. This hybrid role balances in-office and remote work while delivering production-ready data solutions.

Qualifications

• 3+ years in data engineering, analytics engineering, or data warehouse management.
• At least 1 year of hands-on experience building out data pipelines on GCP (BigQuery, Cloud Storage, Cloud Composer, or Dataflow).
• Strong SQL skills (joins, window functions) plus solid Python for scripting.
• Experience moving data off legacy stores into modern cloud data warehouses using dbt, Airflow, or custom scripts.
• BS in Computer Science, Data Engineering, Information Systems, or equivalent work experience.
• US Citizenship required due to public sector contract obligations.

Responsibilities

• Write, test, and maintain ETL/ELT pipelines that pull data from various systems into BigQuery and Cloud Storage.
• Design dimensional models, schemas, and data views for fast, cost-effective queries.
• Maintain clean code practices across Git, basic CI/CD, unit tests, and documentation.

Skills

Data engineering

SQL

Python

GCP

ETL pipelines

dbt

Airflow

BigQuery

Data modeling

Education

BS in Computer Science or related field

Tools

dbt

Airflow

Spark/PySpark

Cloud Composer

Git

Job description

Our mission is to radically transform government and healthcare using the Google Cloud Platform. We do this by partnering with our clients and with the Google Cloud team to develop tools that make it easier for our clients to serve their communities.

About Us

Our mission is to radically transform government and healthcare using the Google Cloud Platform. We do this by partnering with our clients and with the Google Cloud team to develop tools that make it easier for our clients to serve their communities.

About the Role

We are looking for a mid-level Data & Migration Engineer to help us untangle legacy data systems and move them over to Google Cloud. In this role, you will work directly alongside client technical teams and our internal engineers to dig into existing databases, write reliable ETL/ELT pipelines, and handle hands‑on data migrations.

If you like building clean data models, figuring out how to move tricky legacy data without breaking things, and seeing your work go straight into production, this team is a great fit.

Key Responsibilities Data Engineering & Architecture

• Write, test, and maintain ETL/ELT pipelines that pull data from various systems and load it into BigQuery and Cloud Storage.
• Design dimensional models, schemas, and data views that keep queries fast and cost-effective.
• Maintain clean code practices across all work, including Git versioning, basic CI/CD, unit tests, and documentation.

Data Migration & Modernization

• Inspect legacy source databases, flat files, and APIs to map out exact field mappings before moving data.
• Run both batch scripts and real-time ingestion pipelines to shift client data out of legacy environments and into GCP.
• Write automated validation scripts to check row counts, checksums, and data types so nothing gets dropped or corrupted in transit.

Analytics & Client Engagement

• Sit down with business stakeholders to unpack messy business logic and translate it into clear technical SQL scripts.
• Work alongside client analysts and architects during sprints to make sure data builds hit project deadlines.
• Build out targeted data marts and reporting layers so client BI tools and downstream platforms can access clean data easily.

Required Qualifications

• 3+ years in data engineering, analytics engineering, or data warehouse management.
• At least 1 year of hands‑on experience building out data pipelines on GCP (BigQuery, Cloud Storage, Cloud Composer, or Dataflow).
• Strong SQL skills (writing complex joins, window functions, and query tuning) plus solid Python for scripting.
• Prior experience moving data off legacy stores (SQL Server, Oracle, Postgres, or CSVs) and into modern cloud data warehouses using dbt, Airflow, or custom scripts.
• BS in Computer Science, Data Engineering, Information Systems, or equivalent work experience.
• US Citizenship required due to public sector contract obligations.

Preferred Qualifications

• GCP Professional Data Engineer certification.
• Previous experience dealing with public sector, higher ed, or healthcare datasets (and their compliance guardrails like HIPAA or FedRAMP).
• Working experience with dbt for transformations or Apache Airflow for orchestration.
• Exposure to Spark/PySpark for processing large datasets.
• Familiarity with prepping raw data feeds for ML models or LLM ingestion.

Conditions of Employment

The position is an excepted appointment subject to background investigation and drug screen. Due to the nature of our clients, this position requires US citizenship.

• Job Type: Full-time
• Pay: $90,000.00 – $130,000.00 per year + 10% bonus

Benefits

• Health, Dental, and Vision insurance
• Simple IRA Retirement plan with company match
• Unlimited Paid Time Off (PTO)
• Google Certification reimbursement

Job Location & Travel

• Location: Denver, Colorado area (Wheat Ridge, CO office)
• Hybrid Schedule: ~50% in-office/client site, 50% remote (up to 5% travel)