Lead Data Engineer - Real-Time Data Pipelines & Cloud Tech

Tiger Analytics Inc.; Richmond (VA); On-site; USD 150,000 - 190,000; Full time

Job summary

Tiger Analytics is seeking an experienced Lead Data Engineer to design, build, and optimize scalable data platforms and real-time data solutions. The ideal candidate will have strong hands‑on expertise in Python, SQL, cloud platforms, distributed data processing, streaming technologies, and modern cloud data warehouses.

Key responsibilities include leading design and development of scalable pipelines, implementing data solutions on AWS/Azure/GCP, and collaborating with architects and

Qualifications

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

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
• 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.

Skills

Leadership

Strategic thinking

Communication

Problem solving

Mentoring

Tools

Python

SQL

AWS

GCP

Azure

Spark

Kafka

Hadoop

EMR

MapReduce

Snowflake

Databricks

Redshift

Job description

Tiger Analytics is seeking an experienced Lead Data Engineer to design, build, and optimize scalable data platforms and real-time data solutions. The ideal candidate will have strong hands‑on expertise in Python, SQL, cloud platforms, distributed data processing, streaming technologies, and modern cloud data warehouses.

Key responsibilities include leading design and development of scalable pipelines, implementing data solutions on AWS/Azure/GCP, and collaborating with architects and