Senior Data Engineer

Raas Infotek; Plano (TX); On-site; USD 140,000 - 170,000; Full time

Benefits offered by this job

Relocation support

Job summary

Raas Infotek LTD in Texas, USA seeks an experienced Senior Data Engineer to design, build, and maintain scalable data pipelines. You will work with Python, SQL, PySpark, and cloud platforms to deliver reliable data solutions.

Responsibilities include building ETL/ELT processes, integrating data sources, maintaining data warehouses, monitoring quality, and collaborating with analysts and scientists.

Qualifications

• 11+ years of data engineering experience.
• Strong hands-on experience with ETL/ELT, data pipelines, and data warehousing.
• Proficient in Python, SQL, and PySpark for scalable data solutions.

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

Informatica

SQL Server

Oracle

PostgreSQL

MySQL

Apache Airflow

Git

CI/CD

Docker

Kubernetes

Data quality

Power BI

Tableau

Tools

Airflow

Git

CI/CD

Docker

Kubernetes

Snowflake

Databricks

Power BI

Tableau

Informatica

AWS Glue

Azure Data Factory

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