Senior Data Engineer I
American Express6 hours ago
Phoenix, AZ, USASenior
Base Salary
$123k - $215k/yr
Responsibilities
- Mentor and coach Data Engineers while promoting technical excellence and knowledge sharing.
- Lead the design and implementation of scalable logical and physical data models.
- Engineer, administer, and optimize relational, NoSQL, distributed, and cloud-native database platforms.
- Drive database performance tuning, execution plan analysis, indexing, partitioning, capacity planning, and workload management.
- Design highly available architectures, replication strategies, backup and recovery processes, and disaster recovery solutions.
- Develop Infrastructure as Code and automation frameworks for database platform provisioning and management.
- Design and optimize Big Data platforms and distributed data management strategies.
- Integrate data platforms with cloud-native applications, CI/CD pipelines, containerized environments, and data engineering ecosystems.
- Establish standards for data architecture, security, governance, automation, and operational practices.
- Lead root cause analysis for production incidents and improve reliability, observability, performance, and operational resilience.
- Evaluate emerging technologies and influence modernization initiatives across enterprise data platforms.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline, or equivalent professional experience; a master's degree is preferred.
- At least 8 years of experience designing, developing, administering, and optimizing large-scale enterprise database platforms and data engineering solutions.
- Expertise with Oracle, PostgreSQL, and MySQL, plus strong experience with MongoDB, Couchbase, Cassandra, Redis, or equivalent NoSQL platforms.
- Experience with distributed databases such as YugabyteDB and Cassandra; SingleStore experience is highly preferred.
- Experience with in-memory databases such as SingleStore, Redis, or Apache Ignite.
- Experience with cloud-native database and DBaaS/SaaS offerings on AWS and Google Cloud Platform, including Amazon RDS, Aurora, DynamoDB, Cloud SQL, BigQuery, Bigtable, MongoDB Atlas, Couchbase, and Yugabyte.
- Expertise in database performance tuning, data modeling with tools such as ER/Studio or ERwin, and OLTP, OLAP, data warehouse, data mart, and Big Data platforms.
- Experience building ETL/ELT, data integration, and distributed processing solutions with technologies such as Apache Spark and Kafka.
- Strong programming skills in Python and SQL; Java or other object-oriented languages are a plus.
- Experience with Terraform, Docker, Kubernetes, Git, Linux, shell scripting, CI/CD, ServiceNow, Jira, and Agile delivery practices.
- Knowledge of distributed systems, data lakes, storage architectures, XML, JSON, metadata management, observability, monitoring, SRE principles, and production operations.
- Working knowledge of AI, GenAI, LLM integration, vector databases, RAG, and AI-assisted data engineering workflows.
- Strong analytical, troubleshooting, communication, collaboration, technical leadership, and mentoring skills.
Tech Stack
Amazon DynamoDBApache CassandraApache KafkaApache SparkAWSCouchbaseDockerGitGoogle BigQueryGoogle Cloud PlatformJavaKubernetesLinuxMongoDBMySQLPostgreSQLPythonRedisSingleStoreSQLTerraform
Categories
Data Engineering
About American Express
American Express builds a global payments network and issues consumer, small-business, and corporate cards, plus merchant acquiring and travel services. Revenue comes from card fees, interest and lending, discount/merchant fees, and network services. Founded in 1850 and headquartered in New York City, it operates the Amex acceptance network worldwide and offers co-branded cards and membership rewards across millions of cardmembers and merchants; ticker NYSE: AXP.