Lead Data Engineer - AWS

ZipRecruiter; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

An established industry player is seeking a Lead Data Engineer to join their dynamic team. In this role, you'll design and maintain scalable data pipelines on AWS, working closely with cross-functional teams to support analytics and machine learning initiatives. This position offers significant career development opportunities in a fast-paced environment, where your expertise in AWS, Databricks, and data engineering will be highly valued. If you're looking to make a substantial impact in the analytics field, this opportunity is perfect for you.

Qualifications

• 10+ years of experience in data processing pipelines.
• Hands-on experience with AWS and Databricks.
• Proficiency in SQL and data modeling.

Responsibilities

• Design and deploy scalable data pipelines on AWS.
• Collaborate with teams to deliver data solutions.
• Optimize data pipelines for performance and cost.

Skills

Data Engineering

AWS Services

Apache Airflow

Databricks

SQL

Apache Spark

CI/CD Pipelines

Data Modeling

Problem Solving

Communication Skills

Tools

Git

AWS Glue

Amazon S3

Amazon Redshift

AWS Lambda

Job description

Job DescriptionJob 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.

As a Lead Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. You will work closely with cross-functional teams to support data analytics, machine learning, and business intelligence initiatives. The ideal candidate will have strong experience with AWS services, Databricks, and Apache Airflow.

Key Responsibilities:

• Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
• Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements.
• Build and maintain orchestration workflows using Apache Airflow to automate data pipeline execution, scheduling, and monitoring.
• Lead the migration of legacy data systems to modern cloud-based architectures.
• Develop and maintain CI/CD pipelines for data workflows.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver scalable data solutions.
• Optimize data pipelines for performance, reliability, and cost-effectiveness, leveraging AWS best practices and cloud- technologies.

Requirements

• 10+ years of experience building and deploying large-scale data processing pipelines in a production environment.
• Hands-on experience in designing and building data pipelines on AWS cloud infrastructure.
• Strong proficiency in AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
• Lead the design, development, and optimization of large-scale data pipelines and data lakehouse architectures using Databricks
• Architect and implement batch and real-time streaming solutions leveraging Apache Spark on Databricks
• Hands-on experience with Apache Airflow for orchestrating and scheduling data pipelines.
• Solid understanding of data modeling, database design principles, and SQL and Spark SQL.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
• Strong problem-solving skills and attention to detail.

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.