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# Senior Data Engineer

- **Company:** Tiger Analytics
- **Location:** Richmond, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Database, Cloud Engineering, Software Quality, Information Engineering, Data Systems, Data Warehousing, Distributed Computing Environment, Distributed Systems, Apache Hadoop, MapReduce, Python (Programming Language), SQL Databases, Data Processing, Snowflake, Apache Spark, Electronic Medical Records, Real Time Data, Apache Kafka, Data Management, Data Pipelines, Amazon Redshift, Databricks
- **Published:** August 20, 2026
- **Apply:** https://www.careerjet.com/jobad/usffd58200f8ce144ec8861bff9d5f2b40

## About the Role

* 10+ years of experience in application/data engineering using Python and SQL.
 * 5+ years of experience working with at least one major public cloud platform: AWS, GCP, or Azure.
 * 5+ years of experience with distributed data processing technologies such as Spark, Kafka, Hadoop, EMR, MapReduce, or equivalent.
 * 5+ years of experience building and supporting real-time data and streaming applications.
 * 5+ years of experience with cloud data warehouses/platforms such as Snowflake, Databricks, or Redshift.
 * 5+ years of experience with data modeling for data warehousing and analytics.
 * Strong understanding of data engineering, distributed computing, data pipelines, and cloud architecture.
 * Strong problem-solving and communication skills with the ability to provide technical leadership.

## Description

* Lead the design and development of scalable batch and real-time data pipelines using Python and SQL.
 * Design and implement data solutions on AWS, Azure, or GCP.
 * Build high-volume data processing solutions using Spark, Kafka, Hadoop, EMR, or equivalent distributed technologies.
 * Develop and optimize real-time and event-driven streaming applications.
 * Design data models and structures supporting enterprise data warehouses and analytics platforms.
 * Work with modern cloud data platforms such as Snowflake, Databricks, and Amazon Redshift.
 * Optimize data pipelines and processing workloads for performance, scalability, reliability, and cost efficiency.
 * Lead technical discussions, design reviews, and provide guidance to other data engineers.
 * Collaborate with architects, product teams, application developers, and business stakeholders to translate requirements into scalable data solutions.
 * Establish engineering best practices around code quality, testing, deployment, monitoring, and data quality


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