Data Engineer

Overview

Remote

$80,000 - $100,000

Full Time

No Travel Required

Skills

Data Processing

Data Governance

Data Integration

Data Integrity

Data Lake

Data Modeling

Cloud Computing

Collaboration

Continuous Delivery

Continuous Integration

Amazon Redshift

Git

ELT

Job Details

Job Title: Data Engineer (5 6 Years Experience)

Location: Remote
Employment Type: Full-Time
Visa: OPT

Job Summary:

We are seeking an experienced Data Engineer with a strong background in building scalable data pipelines, data integration, and cloud-based data platforms. The ideal candidate should have hands-on experience in modern data stack technologies and the ability to design, implement, and optimize data workflows to support analytics and business intelligence initiatives.

Key Responsibilities:

Design, build, and maintain reliable and scalable ETL/ELT data pipelines using modern data platforms.
Integrate structured and unstructured data from multiple internal and external data sources.
Work with cloud data services (Azure / AWS / Google Cloud Platform) to develop and manage data solutions.
Collaborate with data analysts, scientists, and business teams to ensure data availability, quality, and governance.
Optimize data processing for performance, scalability, and cost efficiency.
Ensure data security, privacy, and compliance with organizational standards.
Monitor and troubleshoot data pipeline issues, ensuring high availability and data integrity.
Implement best practices for version control, CI/CD, and infrastructure automation.

Required Skills & Qualifications:

Bachelor s degree in Computer Science, Information Technology, or related field.
5 6 years of experience as a Data Engineer or similar role.
Strong knowledge of SQL and at least one programming language (Python, Scala, or Java).
Hands-on experience with one or more cloud platforms (Azure Data Factory / AWS Glue / Google Cloud Platform Dataflow).
Experience with data warehousing technologies (e.g., Snowflake, Synapse, Redshift, BigQuery).
Familiarity with data lake architectures and streaming technologies (Kafka, Event Hub, etc.).
Proficiency with ETL/ELT tools, data modeling, and pipeline orchestration (Airflow, Databricks, DBT, etc.).
Strong understanding of data governance, quality, and security best practices.
Experience with CI/CD pipelines, Git, and DevOps principles.

Preferred Qualifications:

Experience with Power BI / Tableau or similar visualization tools.
Familiarity with containerization and orchestration (Docker, Kubernetes).
Knowledge of infrastructure as code (Terraform, CloudFormation).
Exposure to machine learning pipelines or data science workflows is a plus.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.