Data Engineer

Easy Dynamics

$150K — $180K *
US-AnywhereRemote in United States
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Associate's degree or equivalent professional experience.
  • 2+ years of IT technical experience with 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 like Airflow or dbt.
  • Familiarity with distributed data processing frameworks like Spark or Kafka.
  • Experience with cloud data warehouses, such as Snowflake or BigQuery.
  • Proficiency in Python for data engineering tasks.
  • Understanding of data modeling and data quality best practices.

Responsibilities

  • Design, build, and maintain data pipelines (ETL/ELT) for data extraction and loading.
  • Partner with product teams to define data requirements and quality expectations.
  • Work with engineering on pipeline architecture for batch and real-time processing.
  • Write and optimize SQL queries and scripts for data transformation and validation.
  • Monitor pipeline health and troubleshoot failures for data reliability.
  • Support integration of data sources into cloud data warehouses or lakes.
  • Help define future data architecture to manage increased volume and new analytics use cases.
  • Document data flows, schemas, and pipeline logic for reference.

Benefits

  • Professional development opportunities.
  • Access to cutting-edge technology and tools.
  • Collaborative work environment with Product Management and Engineering teams.
  • Potential to impact future data architecture and analytics use cases.
Full 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

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