Senior Data Engineer: Build Scalable Cloud ETL Pipelines

Raas Infotek LTD; Texas City (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Raas Infotek LTD in Texas, USA seeks a Senior Data Engineer to build scalable data pipelines, integrate data from diverse sources, and ensure data quality and reliability. Strong hands-on skills in Python, SQL, PySpark, and modern cloud data stack are required.

The role focuses on ETL/ELT design, data warehousing, and working with platforms like Snowflake, Databricks, Redshift or BigQuery, plus orchestration with Airflow and containerized deployments using Docker/Kubernetes.

Qualifications

• 11+ years of IT experience with strong data engineering background.
• Hands-on with data pipelines, cloud platforms and ETL/ELT processes.
• Excellent analytical, problem-solving, and communication skills.

Responsibilities

• Design, develop, and maintain scalable data pipelines.
• Build and optimize ETL/ELT processes using Python, SQL, and PySpark.
• Integrate data from databases, APIs, and other sources.
• Develop and maintain data warehouses and data models.
• Monitor data quality and troubleshoot pipeline issues.
• Collaborate with data analysts, data scientists, and business teams.

Skills

Python

SQL

PySpark

ETL/ELT

Data pipelines

Data modeling

Data warehousing

Apache Spark

Hadoop

Hive

Kafka

AWS

Azure

GCP

Snowflake

Databricks

Redshift

BigQuery

AWS Glue

Azure Data Factory

In formatica

SQL Server

Oracle

PostgreSQL

MySQL

Airflow

Git

CI/CD

Docker

Kubernetes

Data quality

Power BI

Tableau

Tools

Snowflake

Databricks

Redshift

BigQuery

AWS Glue

Azure Data Factory

Informatica

Airflow

Git

CI/CD

Docker

Kubernetes

Power BI

Tableau

Job description

Raas Infotek LTD in Texas, USA seeks a Senior Data Engineer to build scalable data pipelines, integrate data from diverse sources, and ensure data quality and reliability. Strong hands-on skills in Python, SQL, PySpark, and modern cloud data stack are required.

The role focuses on ETL/ELT design, data warehousing, and working with platforms like Snowflake, Databricks, Redshift or BigQuery, plus orchestration with Airflow and containerized deployments using Docker/Kubernetes.