Senior Data Engineer

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

Senior Data Engineer - Job Description

Location: Texas, USA
Experience: 11+ Years
Job Type: W2
Relocation: Candidates willing to relocate are welcome.

Job Summary

We are looking for an experienced Senior Data Engineer with strong hands-on experience in data engineering, ETL pipelines, cloud platforms, and big data technologies. The candidate will be responsible for building scalable data solutions, integrating data from multiple sources, and ensuring data quality and reliability.

Required Technologies

• Programming: Python, SQL, PySpark.
• Data Engineering: ETL/ELT, data pipelines, data modeling, data warehousing.
• Big Data: Apache Spark, Hadoop, Hive, Kafka.
• Cloud Platforms: AWS, Azure, or Google Cloud Platform.
• Data Platforms: Snowflake, Databricks, Amazon Redshift, or Google BigQuery.
• ETL Tools: AWS Glue, Azure Data Factory, Informatica, or similar tools.
• Databases: SQL Server, Oracle, PostgreSQL, or MySQL.
• Workflow Orchestration: Apache Airflow or similar tools.
• DevOps: Git, CI/CD, Docker, and Kubernetes.
• Data Quality: Data validation, data cleansing, monitoring, and performance optimization.
• Reporting: Power BI or Tableau is a plus.

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.
• Optimize data processing performance and reliability.
• Collaborate with data analysts, data scientists, and business teams.

Preferred Domain Experience

Experience in one or more of the following domains is preferred:

• Banking and Financial Services
• Healthcare
• Insurance
• Retail and E-commerce
• Telecommunications

Candidate Requirements

• 11+ years of overall IT experience with strong data engineering experience.
• Hands-on experience with data pipelines, cloud platforms, and ETL/ELT processes.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently and collaborate with technical teams.