Lead Data Engineer II — AI & Data Platform Leader

Relha LLC; Philadelphia (Philadelphia County); Hybrid; USD 130,000 - 180,000; Full time

Benefits offered by this job

Disability accommodations

Comprehensive benefits

Job summary

Deloitte’s GPS practice seeks a Lead Data Engineer II in the US to design and optimize batch and streaming data pipelines for large-scale platforms. You will translate business and technical needs into scalable data models and engineering solutions while leading delivery across workstreams.

You will integrate data from diverse enterprise systems and cloud environments to support analytics and AI use cases, mentor teammates, and ensure reliability and quality at scale.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a technical field, or equivalent experience.
• 6+ years designing, building, and maintaining data pipelines and cloud data platforms.
• 4+ years Python, SQL, and distributed processing experience.
• 3+ years cloud platforms (AWS, Azure, or GCP).
• 2+ years leading data engineering workstreams and pipelines.
• Willingness to travel ~25% on average and provide production data solutions.

Responsibilities

• Designing, building, and optimizing batch and streaming data pipelines for large-scale platforms.
• Translating requirements into scalable data models and engineering solutions.
• Leading technical delivery across data engineering workstreams, including code reviews.
• Integrating data from multiple enterprise sources and cloud environments.
• Supporting testing, deployment, monitoring, and data quality improvements.

Skills

Python

SQL

Data pipelines

Cloud platforms

Leadership

Communication

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent

Tools

Databricks

Snowflake

Apache Airflow

Job description

Deloitte’s GPS practice seeks a Lead Data Engineer II in the US to design and optimize batch and streaming data pipelines for large-scale platforms. You will translate business and technical needs into scalable data models and engineering solutions while leading delivery across workstreams.

You will integrate data from diverse enterprise systems and cloud environments to support analytics and AI use cases, mentor teammates, and ensure reliability and quality at scale.