Data Engineer

EdgeQ Technologies Private Limited; Dallas (TX); On-site; USD 100,000 - 160,000; Full time

Job summary

EdgeQ Technologies Private Limited seeks a Data Engineer to design, develop, and maintain scalable data pipelines and infrastructure to enable analytics and ML across the org. You will collaborate with data scientists, analysts, and engineers to build robust data warehouses, implement ETL/ELT workflows, and manage cloud data platforms (AWS/Azure/GCP) ensuring data quality and governance.

You will collaborate with data scientists, analysts, and engineers to build robust data warehouses, implement

Qualifications

• Bachelor’s degree in Computer Science, IT, Engineering or related field.
• 2-9 years of professional experience in data engineering.
• Strong programming skills in Python, SQL and experience with Spark or PySpark.
• Hands-on experience with cloud platforms (AWS/Azure/GCP) and data warehouse technologies.
• Proficiency in building and maintaining production-grade ETL pipelines.

Responsibilities

• Design, develop and maintain scalable data pipelines and ETL/ELT workflows.
• Build and optimize data warehouses, lakes, and lakehouse architectures.
• Implement batch and real-time data processing using Python, SQL and Spark.
• Manage cloud-based data infrastructure on AWS, Azure or GCP.
• Ensure data quality, security, governance and monitor pipeline performance.
• Collaborate with analytics, AI/ML and engineering teams to deliver reliable data solutions.

Skills

Python programming

SQL

Spark / PySpark

Education

Bachelor's degree in CS/IT/Engineering or related field

Tools

dbt

Airflow

Snowflake

Databricks

Kafka

Job description

We are seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines and infrastructure. You will collaborate with data scientists, analysts, and engineering teams to enable analytics and machine learning across the organization.

Key responsibilities

• Design, develop and maintain scalable data pipelines and ETL/ELT workflows.
• Build and optimize data warehouses, lakes, and lakehouse architectures.
• Implement batch and real-time data processing using Python, SQL and Spark.
• Manage cloud-based data infrastructure on AWS, Azure or GCP.
• Ensure data quality, security, governance and monitor pipeline performance.
• Collaborate with analytics, AI/ML and engineering teams to deliver reliable data solutions.

Required qualifications

• Bachelor’s degree in Computer Science, IT, Engineering or related field.
• 2-9 years of professional experience in data engineering.
• Strong programming skills in Python, SQL and experience with Spark or PySpark.
• Hands-on experience with cloud platforms (AWS/Azure/GCP) and data warehouse technologies.
• Proficiency in building and maintaining production-grade ETL pipelines.

Nice to have

• Experience with modern data stack tools such as dbt, Airflow, Snowflake or Databricks.
• Knowledge of real-time streaming technologies like Kafka.
• Relevant cloud certifications.