Director - Data Engineering - Lumi at American Express Company South Africa

Chennai, tamil nadu, India -

Full Time

Start Date

Immediate

Expiry Date

19 Apr, 26

Salary

0.0

Posted On

19 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Cloud Automation, Automation Frameworks, Data Migration, GCP Services, Distributed Data Frameworks, Metadata Management, CI/CD, Infrastructure-As-Code, Observability, Stakeholder Management, Agile Methodologies, Data Governance, Validation Tools, Automation Pipelines, Engineering Standards

Industry

Financial Services

Description

At American Express, our culture is built on a 175-year history of innovation, shared values, and Leadership Behaviors — and an unwavering commitment to back our customers, colleagues, and communities. As part of Team Amex, you’ll experience this powerful backing through holistic well-being, continuous learning, and opportunities to grow as a leader and define the future of American Express. We are seeking a strategic and hands-on Director of Data Engineering to lead the Lumi Migration and Accelerator Engineering initiatives, based in Chennai, India. This leader will drive Lumi’s data modernization journey by developing automation frameworks, accelerators, and validation tools that power large-scale migrations from legacy systems to Lumi’s cloud-native (GCP) platform. The ideal candidate combines deep engineering expertise with platform vision and strong execution capabilities to deliver automation-first, scalable, and resilient data transformation solutions. This role will closely partner with the Lumi Product team on the enterprise data migration roadmap, the UDM team to leverage and enhance the Data Ingestion Framework (DIF), and the Lumi Platform team to coordinate platform-level engineering and integration efforts. Key Responsibilities Lead design and delivery of Lumi data accelerators automating migration, transformation, and validation at scale. Own the end-to-end migration lifecycle — from planning and execution to validation and post-migration stabilization. Build reusable tools, APIs, and frameworks that standardize modernization workflows and enable self-service onboarding. Develop automation pipelines for metadata extraction, schema mapping, lineage, and code conversion to GCP-native services (BigQuery, Dataproc, Dataflow). Collaborate with Lumi Product, UDM, and Platform teams to ensure alignment of frameworks, governance, and platform capabilities. Define and enforce engineering standards for scalability, performance, and cost efficiency. Create validation and reconciliation frameworks ensuring accuracy, completeness, and data quality during and after migration. Integrate data governance, lineage, and compliance controls across all automation pipelines. Implement observability and reliability engineering practices using Prometheus, Grafana, or Stackdriver. Oversee migration operations, ensuring SLA adherence, data integrity, and proactive incident management. Define and track KPIs/OKRs for automation adoption, migration velocity, and operational excellence. Mentor and develop high-performing teams focused on automation, GCP engineering, and platform innovation. Foster a culture of engineering excellence, collaboration, and continuous improvement across Lumi’s global teams. Minimum Qualifications 10–15 years in Data Platform Engineering, Software Development, or Cloud Automation, leading large-scale data migration or tooling initiatives. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Proven expertise in automation frameworks, validation tools, and data migration engineering. Strong experience with distributed data frameworks (Spark, Beam, Flink) and GCP services (BigQuery, Dataproc, Dataflow, GCS). Background in metadata management, lineage, and governance integration (Collibra, Apache Atlas, Informatica). Proficiency in CI/CD and Infrastructure-as-Code (Terraform, Jenkins, Argo, GitHub Enterprise). Solid understanding of observability, SRE, and fault-tolerant design for large-scale data platforms. Strong stakeholder management skills and proven ability to lead Agile, globally distributed engineering teams. Preferred Qualifications Experience in BFSI or FinTech data modernization or cloud migration programs. Exposure to AI/ML data pipelines for analytics, fraud, or risk modeling. Experience implementing FinOps and cloud cost-optimization strategies. Knowledge of data compliance and risk management in enterprise environments. GCP Professional Data Engineer or Cloud Architect certification. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: 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 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. 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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Responsibilities

Lead the design and delivery of Lumi data accelerators, automating migration, transformation, and validation at scale. Oversee the end-to-end migration lifecycle, ensuring data integrity and adherence to SLAs.