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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 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.