Remote Data Engineer — Pipelines, ML Features & CI/CD

Eliassen Group; Bismarck (ND); Remote; USD 83,000 - 96,000; Full time

Benefits offered by this job

Medical, Dental, Vision benefits

401k with company matching

Life insurance

Job summary

Eliassen Group seeks a Data Engineer to work remotely, owning data pipelines and the tech stack across the SDLC. You will build scalable pipelines in Azure/GCP ecosystems, implement ML feature engineering with Vertex AI, and ensure quality with automated tests and CI/CD.

Responsibilities include modernizing data assets, documenting interfaces, and driving delivery of data solutions across SQL, NoSQL, and streaming platforms.

Qualifications

• 4+ years of data development experience with SQL and NoSQL.
• 3+ years building data pipelines and workflows.
• 2+ years Python development and ML feature engineering.
• Experience with CI/CD pipelines and automated testing.
• Knowledge of ETL, data warehousing, and Agile (Scrum).
• Familiarity with GCP or Databricks and Spark concepts.

Responsibilities

• Design, build, and maintain scalable data pipelines for ingestion and transformation using Kafka and Databricks.
• Modernize data assets across SQL, NoSQL, cloud, and real-time platforms.
• Develop feature engineering pipelines for ML using Vertex AI and BigQuery ML.
• Create automated testing frameworks for data quality and CI/CD pipelines.
• Draft architecture diagrams and document interfaces for data solutions.
• Own systems and drive features to completion across internal and external apps.

Skills

SQL

NoSQL

Python

Kafka

Databricks

BigQuery ML

Vertex AI

CI/CD

Git

ETL

Agile/Scrum

Spark

GCP

Data pipelines

Tools

Kafka

Databricks

BigQuery

Vertex AI

GitHub Actions

Spark

Cloud Storage

Dataflow

Job description

Eliassen Group seeks a Data Engineer to work remotely, owning data pipelines and the tech stack across the SDLC. You will build scalable pipelines in Azure/GCP ecosystems, implement ML feature engineering with Vertex AI, and ensure quality with automated tests and CI/CD.

Responsibilities include modernizing data assets, documenting interfaces, and driving delivery of data solutions across SQL, NoSQL, and streaming platforms.