Data Engineer

Raas Infotek; Plano (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Raas Infotek in Plano, TX seeks a Senior Data Engineer with 12+ years to design scalable data platforms and cloud pipelines. You will build batch and streaming data solutions, optimize workloads, and mentor junior engineers.

Responsibilities include developing ETL/ELT processes, data models, data warehouses and lakehouses, ensuring data quality, governance, and security across cloud environments (AWS/Azure/GCP). Strong SQL, Python, Spark, and CI/CD skills are essential.

Qualifications

• 12+ years of experience in Data Engineering.
• Strong expertise in Python, SQL, ETL/ELT.
• Advanced experience with AWS / Azure / Google Cloud Platform.
• Hands-on experience with Snowflake, Databricks, or equivalent cloud data platforms.
• Strong knowledge of data warehousing and dimensional data modeling.
• Experience with Spark / PySpark.
• Expertise in Azure Data Factory / AWS Glue / similar orchestration tools.
• Experience developing batch and real-time data pipelines.
• Strong knowledge of Kafka or other streaming technologies.
• Experience with Data Lake / Data Lakehouse architectures.
• Strong understanding of data quality, validation, governance, and security.
• Experience with CI/CD, Git, Docker, and Kubernetes.
• Performance tuning and optimization of large-scale data workloads.
• Excellent communication and stakeholder-management skills.

Responsibilities

• Design and develop scalable data pipelines and ETL/ELT processes.
• Build and maintain cloud-based data platforms.
• Develop complex SQL queries and optimize data-processing workloads.
• Implement data integration across multiple sources.
• Develop batch and streaming data solutions.
• Design data models, data warehouses, and lakehouse architectures.
• Ensure data quality, reliability, security, and governance.
• Collaborate with architects, analysts, developers, and business stakeholders.
• Troubleshoot production data issues and improve pipeline performance.
• Mentor junior and mid-level data engineers.
• Support modernization and migration of legacy data platforms to cloud environments.

Skills

Python

SQL

ETL/ELT

AWS

Azure

GCP

Snowflake

Databricks

Spark

Azure Data Factory

AWS Glue

Data Lakehouse

Kafka

CI/CD

Docker

Kubernetes

Data Quality

Security

Communication

Tools

Snowflake

Databricks

Airflow

Kafka

Git

Docker

Kubernetes

CI/CD

Job description

Job Description

We are seeking a highly experienced Senior Data Engineer with 12+ years of expertise in designing, developing, and optimizing scalable data platforms, pipelines, and cloud-based data solutions.

Role:

Senior Data Engineer

Experience:

12+ Years

Job Type:

W2

Required Skills

• 12+ years of experience in Data Engineering
• Strong expertise in Python, SQL, ETL/ELT
• Advanced experience with AWS / Azure / Google Cloud Platform
• Hands-on experience with Snowflake, Databricks, or equivalent cloud data platforms
• Strong knowledge of data warehousing and dimensional data modeling
• Experience with Spark / PySpark
• Expertise in Azure Data Factory / AWS Glue / similar orchestration tools
• Experience developing batch and real-time data pipelines
• Strong knowledge of Kafka or other streaming technologies
• Experience with Data Lake / Data Lakehouse architectures
• Strong understanding of data quality, validation, governance, and security
• Experience with CI/CD, Git, Docker, and Kubernetes
• Performance tuning and optimization of large-scale data workloads
• Excellent communication and stakeholder-management skills

Key Responsibilities

• Design and develop scalable data pipelines and ETL/ELT processes
• Build and maintain cloud-based data platforms
• Develop complex SQL queries and optimize data-processing workloads
• Implement data integration across multiple sources
• Develop batch and streaming data solutions
• Design data models, data warehouses, and lakehouse architectures
• Ensure data quality, reliability, security, and governance
• Collaborate with architects, analysts, developers, and business stakeholders
• Troubleshoot production data issues and improve pipeline performance
• Mentor junior and mid-level data engineers
• Support modernization and migration of legacy data platforms to cloud environments