Information Technology_USA - USA_Engineer

Real Soft•Jacksonville, FL

5d•Onsite

About The Position

We are seeking a Lead Data Engineer / Architect to spearhead our AI & Marketing Data Modernization efforts. This role involves modernizing legacy systems and scaling data platforms within the marketing, advertising, or growth analytics ecosystems. The ideal candidate will have extensive experience in data engineering and platform engineering, with a strong focus on leveraging AI/ML in data workflows and understanding modern engineering practices.

Requirements

8-12 years of experience in data engineering / platform engineering.
Proven experience working in marketing, advertising, or growth analytics ecosystems.
Strong track record of modernizing legacy systems and scaling data platforms.
Strong expertise in Spark, Databricks, Delta Lake, and distributed data systems.
Deep understanding of data modeling for analytics and marketing use cases.
Proficiency in Python (PySpark) and SQL.
Experience with data pipeline frameworks.
Hands-on exposure to AI/ML in data workflows (predictive analytics, automation, anomaly detection).
Experience with data observability, governance, and automation tools.
Experience with ad platforms (TikTok, Snap, Google Ads, Meta, etc.).
Experience with event tracking and user behavior data.
Experience with attribution models and cohort analysis.
Experience with campaign performance analysis.
Understanding of real-time analytics and experimentation platforms.
Experience with cloud data services on AWS, Azure, or GCP.
Experience with DevOps practices: CI/CD, Infrastructure-as-Code, Git-based workflows.
Experience with Databricks (6-8 years required).

Nice To Haves

Familiarity with GenAI / Agentic AI use cases in engineering productivity.

Responsibilities

Lead data engineering and platform engineering initiatives.
Modernize legacy systems and scale data platforms.
Design and implement data models for analytics and marketing use cases.
Develop and maintain data pipelines using Spark, Databricks, Delta Lake, and Python (PySpark).
Integrate AI/ML capabilities into data workflows for predictive analytics, automation, and anomaly detection.
Explore and implement GenAI/Agentic AI use cases for engineering productivity.
Implement data observability, governance, and automation tools.
Work with marketing data ecosystems, including ad platforms, event tracking, user behavior data, attribution models, and campaign performance.
Develop real-time analytics and experimentation platforms.
Design and implement cloud-based data architectures (Lakehouse, streaming pipelines, event-driven systems) on AWS, Azure, or GCP.
Utilize DevOps practices including CI/CD, Infrastructure-as-Code, and Git-based workflows.