Senior Data Engineer I

Joining Amex Tech means discovering and shaping your contribution to something

big. Here, you can work alongside talented tech teams and build a unique career

with the Powerful Backing of American Express. With a range of opportunities to

work with the latest technologies, and a commitment to back the broader

engineering community through open source, our mission is to power your success.

Because Amex Tech is powered by our technology, our culture, and our colleagues.

Senior Data Engineer I is responsible for the architecture, design, engineering,

and optimization of enterprise-scale data platforms that power mission-critical

business capabilities. This role transforms logical data architectures into

scalable, resilient, and secure physical implementations across relational,

NoSQL, distributed, and cloud-native database technologies.

The Senior Data Engineer drives technical excellence by leading database

architecture, administration, performance optimization, high availability,

disaster recovery, and operational resiliency initiatives. Leveraging deep

expertise in large-scale database systems, the role ensures optimal performance,

scalability, security, and reliability while delivering highly available,

cloud-native data solutions.

Working closely with Product, Architecture, Platform Engineering, and Business

stakeholders, the Senior Data Engineer leads the adoption of modern data

engineering practices, automation, Infrastructure as Code (IaC), and emerging

database technologies. The role is instrumental in advancing enterprise data

platforms through sophisticated data modeling, query optimization, partitioning,

indexing, and distributed data management strategies, enabling high-performance,

data-driven applications at scale.

RESPONSIBILITIES

* Mentor and coach Data Engineers while fostering a culture of technical

excellence, innovation, knowledge sharing, and continuous improvement across

engineering teams.

* Lead and actively contribute within Agile teams, partnering with Product,

Architecture, and Business stakeholders to deliver scalable, high-quality

data solutions and prioritize work across sprint cycles.

* Evaluate emerging database technologies and platform capabilities, driving

the adoption of modern database features, cloud-native services, and

engineering best practices across the organization.

* Design and implement scalable logical and physical data models that support

high-performance, resilient, and secure enterprise data platforms.

* Engineer, administer, and optimize relational, NoSQL, distributed, and

cloud-native database platforms, ensuring scalability, reliability, and

operational excellence.

* Lead database performance optimization initiatives, including SQL tuning,

execution plan analysis, indexing, partitioning, storage optimization,

capacity planning, and workload management.

* Design and maintain highly available database architectures, replication

strategies, backup and recovery processes, and disaster recovery solutions to

ensure business continuity.

* Establish and enforce enterprise standards for data architecture, database

security, governance, automation, and operational best practices.

* Develop Infrastructure as Code (IaC) solutions and automation frameworks to

provision, configure, deploy, and manage database platforms efficiently.

* Design and optimize Big Data platforms by implementing advanced data

modeling, partitioning, indexing, and distributed data management strategies.

* Partner with cross-functional engineering teams to integrate data platforms

with cloud-native applications, CI/CD pipelines, containerized environments,

and modern data engineering ecosystems.

* Collaborate closely with Product, Architecture, Security, and Business teams

to align data platform capabilities with strategic business objectives and

technology roadmaps.

* Lead root cause analysis for complex production incidents and drive

continuous improvements in database reliability, observability, performance,

and operational resilience.

* Influence technical direction by evaluating new technologies, establishing

engineering standards, and driving modernization initiatives across

enterprise data platforms.

QUALIFICATIONS

Education:

* Bachelor's degree in Computer Science, Computer Engineering, Information

Systems, or a related technical discipline; Master's degree preferred or

equivalent professional experience.

Required Experience:

* 8+ years of experience designing, developing, administering, and optimizing

large-scale (TB/PB) enterprise database platforms and data engineering

solutions.

* Expert-level experience with relational databases including Oracle,

PostgreSQL, and MySQL.

* Strong experience with NoSQL databases including MongoDB, Couchbase,

Cassandra, Redis, or equivalent distributed NoSQL platforms.

* Experience with distributed databases including YugabyteDB, Cassandra or

equivalent distributed SQL/NoSQL technologies. SingleStore experience is

highly preferred.

* Experience with in-memory databases such as SingleStore, Redis, or Apache

Ignite.

* Extensive experience with cloud-native database platforms and

Database-as-a-Service (DBaaS/SaaS) offerings on AWS and Google Cloud Platform

(GCP), including Amazon RDS, Aurora, DynamoDB, Cloud SQL, BigQuery, Bigtable,

MongoDB Atlas, Couchbase and Yugabyte.

* Demonstrated expertise in database performance tuning, including SQL

optimization, execution plan analysis, indexing, partitioning, optimizer

statistics, concurrency, locking, memory management, replication, storage

optimization, and capacity planning, with measurable production results.

* Strong experience designing logical and physical data models using enterprise

modeling tools such as ER/Studio, ERwin, or equivalent.

* Experience designing and supporting OLTP, OLAP, data warehouse, data mart,

and Big Data platforms.

* Experience building scalable ETL/ELT, data integration, and distributed data

processing solutions using technologies such as Apache Spark and Kafka.

* Strong programming skills in Python and SQL; experience with Java or other

object-oriented languages is a plus.

* Experience with Infrastructure as Code (Terraform), Docker, Kubernetes, Git,

Linux, shell scripting, and modern CI/CD practices.

* Experience with ServiceNow, Jira, or similar ITSM, ticketing, change

management, incident management, and Agile project management platforms.

* Experience working within Agile software delivery methodologies, including

Scrum, Kanban, and Test-Driven Development (TDD).

Technical Knowledge:

* Deep understanding of relational, NoSQL, distributed, and cloud-native

database architectures, including storage engines, indexing strategies, query

optimization, replication, encryption, backup/recovery, high availability

(HA), disaster recovery (DR), and database security.

* Strong knowledge of distributed systems, multi-tier architectures, consensus

algorithms, and scalable data platform design.

* Knowledge of Big Data ecosystems, data lake architectures, and modern data

storage technologies.

* Understanding of XML, JSON, schema design, metadata management, and

open-source database technologies.

* Knowledge of infrastructure and storage architectures, including SAN, NAS,

hyper-converged infrastructure (e.g., Nutanix), and cloud-native storage

solutions.

* Working knowledge of Artificial Intelligence (AI) and Generative AI (GenAI)

technologies, including LLM integration, vector databases,

retrieval-augmented generation (RAG), AI-assisted development, and AI-powered

data engineering workflows.

* Strong understanding of observability, monitoring, SRE principles, and

production operations.

Professional Attributes:

* Self-motivated, highly technical, and results-oriented with a strong sense of

ownership.

* Excellent analytical, troubleshooting, and problem-solving skills.

* Proven ability to diagnose and resolve complex production issues across

database, cloud, and distributed systems.

* Strong communication, collaboration, and technical leadership skills with

experience mentoring engineers and influencing architectural decisions.

* Demonstrated success delivering highly scalable, resilient, secure, and

high-performance enterprise data platforms.

Employment eligibility to work with American Express in the United States is

required as the company will not pursue visa sponsorship for these positions.