Lead 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 ( 2 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 at Client. This 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.

Duties and Responsibilities: (Scope of the role, day to day activities, expected outcomes, highlights any complexities associated with the role)

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 MarTech 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.

• Data Engineering Lead (Marketing)

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.

Work Experience/ Education: (Required work experience and education / preferred experience and education that is beneficial to the role. Work experience can include management experience or any functional expertise where proficiency is necessary to be successful in the role)

• 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, GCP).

• 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, Networking, Serverless, Testing / Test Automation (Unit, Integration, Performance, etc.), WebServices, DevOps, Logging, Monitoring, and Alerting, Containerization, Encryption / Decryption, Data Masking, Cost & Performance Optimization

• Skilled leading and/or participating in system design and architectural activities including technical requirement writing experience and ability to lead collaboration sessions for important design reviews and decisions.

• Proven experience succeeding in complex, matrix and cross-functional projects

• Ability to personally deliver large scale initiatives in a fast-paced environment with high levels of complexity and ambiguity

• Experience and comfort managing indirect teams; scrums, agile cross functional teams, vendor stakeholders

• Strong collaboration skills and the ability to work in a team-based environment including employees, vendors and third-party contractors

• Ability to inspire, influence and collaborate across a wide range of constituents across functions and organizational levels

• Excellent mentoring skills and the desire to contribute to efforts beyond the scope of the day-to-day project work

• Excellent written, presentation and oral communication skills

• Knowledge of technical architecture as a role discipline

Good to have, but not mandatory:

• Experience working with Loyalty Management data, and other Marketing business processes data

• Experience with Campaign Management, Customer Data Platforms, Content Management, Advertising Technology, Personalization Engines as a Solution, etc., Tech Skills:

Data Engineering Lead (Marketing)

• Microsoft Azure Cloud: Azure Data Factory, APIM, Function Apps, Logic Apps, Key Vault, Azure App Insights, Azure SQL, Azure DevOps

• Databases: Azure SQL, Databricks, MongoDB,

• DevOps: GitHub, Azure DevOps, CI/CD Pipelines

• Programming Languages: SQL, PYTHON, SCALA, R

• API Development: Azure APIM, REST APIs, web services, security such as Oauth2, SAML, IDM, open API standards like swaggers, RAML, developer portal,

• API Testing: Postman,

• Log Analytics: Splunk, Dynatrace

• Web/Mobile App Analytics: Google Analytics, Firebase, Google Tag management

• Architecture modeling: Lucid Chart, Visio, ARIS, etc.,

• Software development Experience using SaFe Agile methodologies.