Data Engineer

Easy Dynamics Corporation; North Dakota; On-site; USD 150,000 - 180,000; Full time

Job summary

Easy Dynamics Corporation is seeking a Data Engineer to design, build, and maintain data pipelines powering reporting and analytics across projects. You will collaborate with Product Management and Engineering to define data requirements and ensure scalable, reliable data solutions for batch and real-time use cases.

The role emphasizes hands-on work with SQL, Python, and modern orchestration tools like Airflow, along with cloud data warehouses and data lakes.

Qualifications

• 2+ years of IT experience with data pipeline development and SQL scripting.
• Ability to obtain and maintain U.S. Government Public Trust or Security Clearance.
• Experience with ETL/ELT design and data quality practices.
• Experience with Airflow, dbt, Spark, or Kafka.
• Experience with cloud data warehouses or lakes (e.g., Snowflake, BigQuery, Redshift, S3).
• Proficiency in Python for data engineering tasks.
• Strong data modeling and data quality fundamentals.

Responsibilities

• Design, build, and maintain data pipelines (ETL/ELT) from sources to targets.
• Collaborate with Product and Eng teams to define data requirements.
• Define architecture for batch and real-time processing.
• Write and optimize SQL and Python for data transformation.
• Monitor pipelines, troubleshoot failures, ensure reliability.
• Integrate data sources into cloud data warehouses or lakes.
• Document data flows and schemas for the team.

Skills

SQL

Python

ETL/ELT design

Data integration

Data quality

Data modeling

Airflow

dbt

Spark

Kafka

Cloud data warehouses

Education

Associate's degree or equivalent experience

Public Trust/Security Clearance eligibility

Tools

Airflow

dbt

Spark

Kafka

Job description

About the role

The Data Engineer is responsible for building and maintaining the data pipelines, storage systems, and processing workflows that power reporting, analytics, and downstream applications across company projects. This role works with Product Management and Engineering to define data requirements and pipeline design, ensuring data solutions are reliable, scalable, and available for both batch and real-time use cases, while helping shape the future data architecture to support increased volume and new use cases.

What you’ll do

• Design, build, and maintain data pipelines (ETL/ELT) that extract, transform, and load data from source systems into target stores.
• Partner with Product Management and downstream teams to define data requirements and data quality expectations.
• Work with Engineering to define pipeline architecture for batch and real-time data processing.
• Write and optimize SQL queries and scripts (Python or similar) to support data transformation and validation.
• Monitor pipeline health, troubleshoot failures, and ensure data availability and reliability.
• Support integration of data sources into cloud data warehouses or data lakes.
• Help define future data architecture to support increased volume, new data sources, and analytics use cases.
• Document data flows, schemas, and pipeline logic for team and stakeholder reference.

Qualifications

• Associate’s degree, or equivalent professional experience.
• 2+ years of IT technical experience, including exposure to data pipeline development, SQL, or scripting.
• Ability to obtain and maintain a U.S. Government Public Trust or Security Clearance.
• Experience with data pipeline orchestration tools such as Airflow, dbt, or similar.
• Familiarity with distributed data processing frameworks, such as Spark or Kafka.
• Experience with cloud data warehouses or lakes, such as Snowflake, BigQuery, Redshift, or S3-based architectures.
• Proficiency in Python for data engineering tasks.
• Understanding of data modeling and data quality best practices.

Salary Range: $150,000-$180,000 based on experience and qualifications

Easy Dynamics is an equal opportunity employer. Applicants are considered for positions without discrimination on the basis of race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, veteran status or any other consideration made unlawful by applicable federal state or local laws.