Senior Data Engineer

Tiger Analytics; Richmond (VA); On-site; USD 150,000 - 230,000; Full time

Job summary

Tiger Analytics is seeking a Lead Data Engineer to design, build, and optimize scalable data platforms and real-time data solutions in a senior capacity. You will lead data pipeline development, collaborate with architects and product teams, and drive best practices for performance and reliability.

The role requires 10+ years in data engineering, strong Python/SQL skills, and extensive cloud experience across AWS/GCP/Azure.

Qualifications

• 10+ years of application/data engineering experience using Python and SQL.
• 5+ years with at least one major public cloud platform: AWS, GCP, or Azure.
• 5+ years with distributed data processing technologies such as Spark, Kafka, Hadoop, EMR, MapReduce, or equivalent.
• 5+ years building and supporting real-time data and streaming applications.
• 5+ years with cloud data warehouses/platforms such as Snowflake, Databricks, or Redshift.
• 5+ years of data modeling for data warehousing and analytics.
• 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

Skills

Python

SQL

Cloud platforms

Distributed data processing

Streaming technologies

Cloud data warehouses

Data modeling

Leadership

Communication

Tools

Spark

Kafka

Hadoop

EMR

MapReduce

Snowflake

Databricks

Redshift

Job description

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. Tiger Analytics is looking for 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

• 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

Requirements

• 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

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.