American Express

„American Express“ yra pasaulinė finansinių paslaugų įmonė, veikianti bankininkystės, finansavimo ir verslo mokėjimų srityse. Jos veikla apima vartotojams, įmonėms ir korporacijoms skirtas kredito korteles, mokėjimų ir prekybininkų paslaugas, taupomąsias sąskaitas, terminuotuosius indėlius ir asmenines paskolas, taip pat apdovanojimų ir kelionių programas, įmonių mokėjimo sprendimus, finansinį švietimą, saugumo paslaugas bei pagalbą kortelių nariams ir prekybininkams.

Darbai įmonėje

Senior Data Engineer

Lead the design and optimization of secure, resilient data platforms at American Express. The role spans database architecture, cloud engineering, performance tuning, and mentoring data engineers.

prieš 14 valandų

Jungtinės Valstijos

Arizona

123 000 $ – 215 250 $ / metai

Hibridinis Visas etatas Vyresnysis specialistas Privaloma Kalba: anglų Duomenų inžinierius

Apache Apvalkalo scenarijų kūrimas AWS BigQuery Cassandra Debesija Docker DynamoDB ETL Google Cloud Platform ITSM Java Kafka Kubernetes Linux MongoDB MySQL NoSQL Oracle Paskirstytosios sistemos Postgres Python Redis ServiceNow Spark SQL Terraform

Aprašymas

Coach data engineers and promote technical excellence, collaboration, and continuous improvement.
Partner with product, architecture, and business teams in Agile delivery, shaping scalable data solutions and sprint priorities.
Assess emerging database technologies and advance cloud services, modern database capabilities, and engineering practices.
Create scalable logical and physical data models for secure, resilient, high-performance enterprise platforms.
Build, operate, and optimize relational, NoSQL, distributed, and cloud-native database systems.
Improve database performance through SQL and query-plan tuning, indexing, partitioning, storage optimization, capacity planning, and workload management.
Design and maintain highly available database architectures, including replication, backup, recovery, and disaster recovery.
Set and uphold standards for data architecture, security, governance, automation, and operations.
Develop infrastructure-as-code solutions and automation frameworks for database platforms.
Design and improve big data platforms through advanced modeling, partitioning, indexing, and distributed data management.
Connect data platforms with cloud applications, CI/CD pipelines, containerized environments, and contemporary data engineering systems.
Align data platforms with strategic goals and technology roadmaps in partnership with product, architecture, security, and business teams.
Investigate complex production incidents and strengthen database reliability, observability, performance, and resilience.
Guide technical direction through technology assessments, engineering standards, and modernization efforts.

Reikalavimai

Bachelor’s degree in computer science, computer engineering, information systems, or a related technical field; a master’s degree is preferred, or equivalent professional experience.
At least 8 years designing, developing, administering, and optimizing large-scale (terabyte/petabyte) enterprise database platforms and data engineering solutions.
Expertise with Oracle, PostgreSQL, and MySQL.
Strong experience with MongoDB, Couchbase, Cassandra, Redis, or comparable distributed NoSQL platforms.
Experience with YugabyteDB, Cassandra, or comparable distributed SQL or NoSQL technologies.
Experience with in-memory databases such as SingleStore, Redis, or Apache Ignite.
Extensive experience with cloud database services and DBaaS/SaaS on AWS and GCP, including Amazon RDS, Aurora, DynamoDB, Cloud SQL, BigQuery, Bigtable, MongoDB Atlas, Couchbase, and Yugabyte.
Expertise in database performance tuning, SQL optimization, execution plan analysis, indexing, partitioning, optimizer statistics, concurrency, locking, memory management, replication, storage optimization, and capacity planning.
Experience creating logical and physical data models with ER/Studio, ERwin, or equivalent tools.
Experience with OLTP, OLAP, data warehouses, data marts, and big data platforms.
Experience building scalable ETL/ELT, data integration, and distributed processing solutions with Apache Spark and Kafka.
Strong Python and SQL skills; Java or another object-oriented language is an advantage.
Experience with Terraform, Docker, Kubernetes, Git, Linux, shell scripting, and CI/CD practices.
Experience with ServiceNow, Jira, or similar IT service management and project management tools.
Experience with Agile practices, including Scrum, Kanban, and test-driven development.
Deep understanding of relational, NoSQL, distributed, and cloud-native database architectures; storage engines, indexing, query optimization, replication, encryption, backup and recovery, high availability, disaster recovery, and database security.
Strong knowledge of distributed systems, multi-tier architectures, consensus algorithms, and scalable data platform design.
Knowledge of big data ecosystems, data lakes, and modern data storage technologies.
Understanding of XML, JSON, schema design, metadata management, and open-source databases.
Knowledge of SAN, NAS, hyperconverged infrastructure, and cloud-native storage.
Working knowledge of AI and generative AI, including LLM integration, vector databases, RAG, AI-assisted development, and AI-enabled data engineering workflows.
Strong understanding of observability, monitoring, SRE principles, and production operations.
Demonstrated ability to diagnose and resolve complex production issues across databases, cloud environments, and distributed systems.
Experience mentoring engineers and influencing architectural decisions.
Visa sponsorship may be available based on business needs, role, cost, and applicable law.

Privalumai

Annual bonus
Benefits

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11 – 50 Darbuotojai

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Atidaryti

1 001 – 5 000 Darbuotojai

B2B Įmonė

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Atidaryti

Senior Data Engineer

Lead the design and optimization of secure, resilient data platforms at American Express. The role spans database architecture, cloud engineering, performance tuning, and mentoring data engineers.

Aprašymas

Reikalavimai

Privalumai

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