Data Engineer
Backend Developer
Python
Amazon Web Services
AWS
Aws Glue
Big Data
Bigdata
CI/CD
Cloud
Cloud Computing
Cloud Data Engineering
Cloud Data Platform
Cloud Data Warehouse
Cloud Infrastructure
Cloud Operations
Cloud Platform
Cloud Platforms
Cloud Technology
Data
Data Analysis
Data Architecture
Data Engineer
Data Engineering
Data Integration
Data Integration Tools
Data Lake
Data Lakehouse
Data Pipeline
Data Platform
Data Processing
Data Warehouse
Database
Databricks
DevOps
Devops Tools
DevSecOps
Engineer
ETL
Informatica
Information Technology (IT)
Infrastructure As Code
IT Services
Programming Language
Programming Languages
Security Devops
Software Development
Spark
Job Description
This hands-on Data Engineer position at Robotics Technologies is based in Plano, TX (onsite). The role centers on designing, building, and maintaining reliable Python and AWS Glue-based data pipelines and connectivity solutions across enterprise data platforms, with support for modern data lake and lakehouse patterns.
Responsibilities
- Build and maintain data pipelines using Python and AWS services.
- Develop data ingestion and connectivity solutions for enterprise data platforms.
- Work with AWS data lake services, including Amazon S3, AWS Glue, and AWS Lake Formation.
- Use AWS CLI and EC2 to support day-to-day data engineering workloads.
- Implement and maintain CI/CD pipelines using Jenkins and Bitbucket.
- Troubleshoot data pipeline issues and improve data quality and reliability.
- Collaborate with platform and engineering teams to support shared data services.
Requirements
- Strong hands-on Python programming experience.
- Practical AWS experience with S3, AWS CLI, EC2, Glue, and Lake Formation.
- Understanding of data lakes and data pipeline development.
- Experience with CI/CD pipelines, including Jenkins and Bitbucket.
- Ability to build, test, troubleshoot, and maintain production data pipelines.
Technologies
The role involves working with Python, AWS, AWS Glue, Amazon S3, Lake Formation, AWS CLI, EC2, Jenkins, and Bitbucket. Additional technologies used include Snowflake, Databricks, Apache Iceberg, AWS Bedrock, Terraform, PySpark, and Apache Spark.
Preferred Skills
- Experience with Snowflake, Databricks, and Apache Iceberg.
- Experience with AWS Bedrock and exposure to AI agentic workflows.
- Experience with Terraform, PySpark, or Apache Spark.
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