Sr Data Engineer

Data Engineering Lead (Marketing) Position Description (General role information, job purpose, main objectives of the role)

Location:

Atlanta, GA Duration: FULL TIME / C2H Mode:
Hybrid ( 3 days a Week)

This Data Engineering Lead (Marketing) position is part of Client IT's Marketing Technology team focused on enabling the development and roll-out of world-class modern Marketing Data Engineering capabilities s role partners with teams responsible for Marketing and Digital Guest Engagement platforms that leverage world-class technology to create personalized, relevant, data-driven experiences. In this role, you will lead teams designing and building Data & BI solutions that capture, explore, transform, and utilize curated data to support Marketing Business Unit's Data-driven transformation journey and decision-making process.

In addition to leading the design and implementation of data products, you will also mentor and develop a team of contingent worker data engineers onsite and offshore.

• Thought Leadership (20%) Provides industry thought leadership to fellow team members across business and technical project dimensions, solving complex business requirements. Proactively considers the future state of the organization and how technology can support these efforts. Advocates and define Marketing Data Engineering vision from a strategic perspective, including internal and external platforms, tools, and systems. Maintains overall Mar Tech industry Data knowledge on latest trends, technology, etc.
• Mentoring (20%) Manage and lead a technical team responsible for data engineering and analysis. focusing on individual's professional development as well as overall team health and technical proficiency on their assigned project tasks. Conducts product work reviews with team members. Serves in the development of team members by actively facilitating new learning opportunities and experiences in the Data Engineering space.
• Development (20%) Design and implement scalable data solutions on Azure platform using Data Factory, Databricks, PySpark, Python and other related services. Build data pipelines and workflows to ingest, transform, and load data from various sources. Develop and maintain data models and schemas for efficient data storage and retrieval. Develop and maintain CI/CD pipelines for automated deployment and testing of data solutions.
  
  Lead development and production deployment of analytic Data and BI products (also potentially pilots and proof of concepts), determining appropriate design strategies and methodologies.
• Collaborations (20%) Collaborate and maintain relationships with cross-functional teams (Cloud Infra, Enterprise Data & IT-SEC) to ensure data solutions meet business requirements. Continuously evaluate and recommend new data technologies and approaches to improve data solutions. Develop business partnerships and influence priorities by identifying solutions that are aligned with current business objectives and closely follow industry trends; understanding how to apply them and sharing knowledge with coworkers.
  
  Communicate with partners, describing technology concepts in ways the business can understand, documenting initiatives in a concise and clear manner. Partner with Enterprise Data management & information security colleagues to ensure the adherence of Data Governance standards for Client.
• Delivery Management (20%) Find creative solutions to challenging problems involving factors with potentially broad implications; reflecting on solutions, measuring impact, and using that information to ideate and optimize. Execute data strategies with an understanding of enterprise architecture, consumption patterns, platforms and application infrastructure. Stay ahead of the impediments to ensure a smooth, on time and in budget, implementation of Data Projects Collect weekly status updates from Dev teams across multiple Data POD teams and consolidate for leadership project health reporting.

Bachelor's degree in computer science, Information Technology or a related study, or equivalent experience 5+ years of hands-on Data Engineering experience with On-Prem and Cloud based Data tools/Platforms, 3+ years of experience in data engineering with expertise specifically in Azure Data Factory, Databricks, PySpark, Python and related services. Proven experience in leading and managing technical teams in data engineering and analysis.

Experience in designing and developing data models and schemas. Strong proficiency in programming languages such as Python. Experience in developing and maintaining CI/CD pipelines for automated deployment and testing. Good understanding of cloud computing and its services (e.g., Azure, AWS, Google Cloud Platform). Excellent problem-solving skills and ability to work in a fast-paced environment.

Experience with the some of the following concepts:
Real-time & Batch Data Processing, Workload Orchestration, Cloud, Data lakes, Data Security,…