Data Engineering Director
4 weeks ago
Lead the Way in Data Engineering
At American Express, we're committed to delivering the best Colleague digital experience. As the Engineering Director of the Digital Workplace Data Platform, you'll play a critical role in leading our engineering teams to develop and enhance the data platform, providing personalization capabilities, analytics, and predictive analysis using AI/ML.
What We're Looking For
We're seeking a seasoned engineering leader with a proven track record of leading remote and distributed product engineering setups. You'll have experience writing software in Python, Scala, or similar, as well as expertise in data structures, algorithms, and software design.
Key Responsibilities
- Create and manage complex distributed data engineering pipelines at scale, ensuring availability, throughput, and security.
- Lead engineering teams and partner with Product Management to enhance the quality and outcomes of data products, including data analytics and visualization.
- Lead the solutioning of AI/ML models on the data to build meaningful insights and predictive analysis.
- Work and collaborate with Product Management and Digital Workplace teams to influence key decisions on architecture and implementation of scalable, reliable, and cost-effective data platforms.
- Bring thought leadership to advance the overall state of technology and customer focus for the platform.
- Manage delivery milestones, deployment cycles, and delivery of the overall Data Platform's roadmap.
- Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with increased data volume.
- Build, inspire, and grow talented engineering teams responsible for designing and building Data Engineering and Analytics suites.
- Build a culture of innovation, ownership, accountability, and customer focus.
- Contribute to the American Express Data Strategy, working with other Technology teams to drive enterprise solutions, define best practices at a company level, and further develop skills and experience outside Digital Workplace.
- Partner with Digital Workplace technology teams to develop the data platform strategy across all products and channels.
- Participate actively and constructively in agile team meetings and application reviews.
- Work directly with and learn from business, product, and engineering leaders across the organization.
- Strengthen collaboration with Industry partners/suppliers for more robust data solutions and market research for innovative solutions in this space.
Professional Qualifications
- Demonstrated experience leading engineering teams in remote and distributed product engineering setups.
- Experience writing software in Python, Scala, or similar, as well as expertise in data structures, algorithms, and software design.
- Experience on various data architectures, latest tools, current and future trends in data engineering space, especially Big Data, Streaming, and Cloud technologies like GCP, AWS, Azure.
- Hands-on experience with Big Data technologies (Spark, Kafka, Hive, etc.) and at least one Big Data implementation on platforms like Cornerstone, Teradata, etc.
- Experience in creating large-scale data engineering pipelines, data-based decision-making, and quantitative analysis.
- Experience with visualization tools like Tableau, Power BI, etc.
- Experience with complex, high-volume, multi-dimensional data, as well as ML/AI models for unstructured, structured, and streaming datasets.
- Advanced experience in writing and optimizing efficient SQL queries with Python, Spark, Hive, Scala handling large data sets in Big-Data & GCP Environments.
- Exposure to Data Science including Predictive Modeling.
- Experience architecting data products in Streaming, Serverless, and Microservices-based Architecture and platform.
- Knowledge of cloud computing, including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems, and content delivery networks.
- Exposure in building cloud-native platforms on modern tech stack: AWS, Java, Spring Framework, RESTful API, and container-based application.
- Exposure in building Predictive models using machine learning through all phases of development, from design through training, evaluation, validation, and implementation.
- Ability to learn new tools and paradigms in data engineering and science.
- Proven experience attracting, hiring, retaining, and leading top engineering talent.
- Creative, passionate, and experienced leader of both people and technology.
- Team Management savvy (e.g., planning, budgetary control, people management, vendor management, etc.).
- Experience with DevOps, reliability engineering, and platform monitoring.
- Well-versed in AGILE, DevOps, and Program Management methods.
- Bachelor's degree with a preference for Computer Science.
What We Offer
We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life.
Benefits include:
- Competitive base salaries.
- Bonus incentives.
- Support for financial-well-being and retirement.
- Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location).
- Flexible working model with hybrid, onsite, or virtual arrangements depending on role and business need.
- Generous paid parental leave policies (depending on your location).
- Free access to global on-site wellness centers staffed with nurses and doctors (depending on location).
- Free and confidential counseling support through our Healthy Minds program.
- Career development and training opportunities.
Equal Opportunity Employer
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.
Background Verification Check
Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.
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