Data Engineering Lead

We are seeking an experienced Data Engineering Lead to drive the design, development, and delivery of scalable cloud-based data solutions. In this role, you will leverage AWS native services, Python, and PySpark to build robust data pipelines and modernize enterprise data platforms. You will play a key role in shaping data architecture, improving data integration, and developing high-performance data products. Working across complex enterprise environments, you will establish engineering standards and ensure the reliability, quality, and scalability of data solutions. You will also provide technical leadership, mentor engineering teams, and collaborate with architecture, technology, and business stakeholders. This is an opportunity to make a meaningful impact in a flexible, remote-first environment while contributing to large-scale data transformation initiatives.

The ideal candidate combines strong hands-on AWS data engineering expertise with proven technical leadership experience. You should demonstrate:

• Strong experience in AWS data engineering, particularly Amazon S3, AWS Glue, and Amazon EMR.

• Proficiency in Python, PySpark, SQL, and ETL/ELT development.

• Expertise in designing, developing, and optimizing large-scale data pipelines.

• Solid experience with enterprise data integration and complex data engineering environments.

• Proven ability to provide technical leadership, establish engineering standards, and conduct code and design reviews.

• Experience mentoring and guiding data engineering teams.

• Experience with Amazon Redshift, Athena, and DynamoDB.

• Knowledge of Apache Iceberg and modern data lake or lakehouse architectures.

• Familiarity with domain-oriented data products and authoritative data sources.

• Exposure to large-scale enterprise data platform modernization initiatives.