This role pays less than
83%
of similar roles. Most pay
$132,670–$214,000
— the shaded band above.
At the midpoint, this role pays about
$124k
versus about
$173k
for comparable roles.
Based on 240 similar postings.
Employer
About State Street
State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody
State Street currently has
176 open roles
on FindRole.
Listed pay typically runs
$120,000–$202,500
across 172 roles with salary data.
As a Cloud Data Engineer, AVP, you will join the team to design, develop, and deliver scalable cloud data solutions using Databricks and AWS. You will collaborate with technology and business partners to modernize data platforms, build reliable data, AI, and machine learning pipelines, and implement secure, cost-effective engineering practices. Your daily work involves assessing infrastructure, defining deployment best practices, and developing migration strategies for various applications. You will utilize a technical stack including Scala, Python, Java, SQL, Apache Airflow, and Docker, while leveraging Databricks features like Delta Live Tables and Unity Catalog. Additionally, you will manage AWS services such as S3, EC2, Kinesis, and Lambda to solve complex problems in database architecture, big data, and advanced analytics, ensuring the successful transition of legacy systems into modern cloud environments.
Design, develop, and deliver scalable cloud data solutions using Databricks and AWS.
Build and optimize data engineering and machine learning pipelines in Databricks using AWS services like S3, Kinesis, and Lambda.
Assess existing infrastructure to identify improvements and recommend cloud-based solutions for performance and scalability.
Develop cost-effective cloud migration strategies and build reusable, efficient data solutions.
Migrate data engineering and machine learning applications from legacy systems to Databricks and AWS.
Define and document best practices for application deployment, cloud infrastructure, and production support.
Create proofs of concept to evaluate the feasibility and value of emerging technologies.
Manage CI/CD pipelines and automation for AWS-based solutions.
What we're looking for
Bachelor’s degree in computer science, information systems, or a related field, or equivalent practical experience.
Five or more years of experience in data engineering, including hands-on work with cloud technologies.
Strong programming experience in Scala, Python, and/or Java for data engineering workloads.
Strong understanding of Databricks architecture, including Data Engineering, Machine Learning, SQL warehouses, Medallion architecture, Delta Live Tables, and Unity Catalog.
Proficiency in AWS services such as S3, EC2, RDS, Kinesis, Kafka, and Lambda.
Strong knowledge of Apache Airflow for workflow orchestration and CI/CD pipelines for AWS deployment.
Experience migrating relational databases, Java and Python applications, machine learning models, and Elasticsearch solutions.
Snowflake
Microsoft Azure
Azure Data Factory
SQL
ETL
ELT
Azure Blob Storage
Azure Data Lake Storage
Informatica Power Center
Power BI
CI/CD
DevOps
Oracle
SQL Server
RBAC