Lead Data Engineer: Real-Time Pipelines & Cloud Data

Tiger Analytics Inc.; Richmond (VA); On-site; USD 140,000 - 200,000; Full time

Job summary

Tiger Analytics Inc. is seeking an experienced Lead Data Engineer to design, build, and optimize scalable data platforms and real-time data solutions.

You will lead and mentor a team, drive end-to-end data pipelines, and collaborate with architects, product teams, and stakeholders to translate requirements into robust data systems. The role requires 10+ years in data engineering with Python/SQL, strong cloud experience (AWS/GCP/Azure), and expertise in Spark, Kafka, Hadoop, and modern cloud

Qualifications

• 10+ years of experience in application/data engineering using Python and SQL.

Responsibilities

• 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

Skills

Leadership

Communication

Problem solving

Mentorship

Tools

Python

SQL

AWS

Azure

GCP

Spark

Kafka

Hadoop

EMR

MapReduce

Snowflake

Databricks

Redshift

Job description

Tiger Analytics Inc. is seeking an experienced Lead Data Engineer to design, build, and optimize scalable data platforms and real-time data solutions.

You will lead and mentor a team, drive end-to-end data pipelines, and collaborate with architects, product teams, and stakeholders to translate requirements into robust data systems. The role requires 10+ years in data engineering with Python/SQL, strong cloud experience (AWS/GCP/Azure), and expertise in Spark, Kafka, Hadoop, and modern cloud