Cloud Data Engineer, AVP

State Street; Boston (MA); On-site; USD 90,000 - 158,000; Full time

Job summary

State Street is seeking a Cloud Data Engineer, AVP, in Boston 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 and ML pipelines, and promote secure, cost-efficient engineering practices.

You will work on defining deployment best practices, building reusable data solutions, and migrating data applications to Databricks and AWS.

Qualifications

• 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.
• AWS and/or Databricks certification is preferred but not required.

Responsibilities

• Assess existing application and data infrastructure, identify improvement opportunities, and recommend cloud-based solutions that enhance performance, scalability, and reliability.
• Define and document best practices for application deployment, cloud infrastructure, and production support.
• Build reusable, efficient, and scalable data solutions, and develop cost-effective cloud migration strategies.
• Design, develop, and optimize data engineering and machine learning pipelines in Databricks using AWS services such as Amazon S3, EC2, API services, RDS, Kinesis, Kafka, and Lambda.
• Partner with IT teams and business stakeholders to migrate data engineering and machine learning applications to Databricks and AWS.
• Manage competing priorities and deliver high-quality solutions within time-sensitive project schedules when needed.
• Evaluate, learn, and support vendor products that contribute to the organization’s data and cloud capabilities.
• Quickly learn emerging technologies and develop proofs of concept to evaluate their value, feasibility, and potential for broader adoption.

Skills

Databricks architecture

Databricks Data Engineering

Machine Learning pipelines

Scala

Python

Java

SQL

AWS

GenAI knowledge

CI/CD

Airflow

Docker

Kubernetes

Data engineering

Education

Bachelor’s degree in computer science or related field

Five+ years of data engineering experience

AWS/Databricks certification preferred

Tools

Docker

Kubernetes

Apache Airflow

Delta Live Tables

Job description

As a Cloud Data Engineer, AVP, you will design, develop and deliver scalable cloud data solutions using Databricks and AWS. You will collaborate with technology and business partners to modernize data platforms, develop reliable data, AI and machine learning pipelines, and help teams adopt secure, efficient, and cost-effective engineering practices.

Education And Experience

• 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.
• AWS and/or Databricks certification is preferred but not required.

What You Will Be Responsible For

• Assess existing application and data infrastructure, identify improvement opportunities, and recommend cloud‑based solutions that enhance performance, scalability, and reliability.
• Define and document best practices for application deployment, cloud infrastructure, and production support.
• Build reusable, efficient, and scalable data solutions, and develop cost‑effective cloud migration strategies.
• Design, develop, and optimize data engineering and machine learning pipelines in Databricks using AWS services such as Amazon S3, EC2, API services, RDS, Kinesis, Kafka, and Lambda.
• Partner with IT teams and business stakeholders to migrate data engineering and machine learning applications to Databricks and AWS.
• Manage competing priorities and deliver high‑quality solutions within time‑sensitive project schedules when needed.
• Evaluate, learn, and support vendor products that contribute to the organization’s data and cloud capabilities.
• Quickly learn emerging technologies and develop proofs of concept to evaluate their value, feasibility, and potential for broader adoption.

What We Value

• Demonstrated decision‑making, analytical, and problem‑solving skills, with the ability to evaluate trade‑offs and recommend practical solutions.
• Strong understanding of Databricks architecture and hands‑on experience with Databricks Data Engineering, Machine Learning, and SQL warehouses.
• Strong programming experience in Scala, Python, and/or Java for data engineering workloads.
• Strong knowledge of Medallion architecture, Delta Live Tables, and Unity Catalog within Databricks.
• Knowledge of GenAI and Agentic AI is a plus.
• Understanding of core AWS services, their use cases, and AWS architecture best practices.
• Hands‑on experience across relevant domains such as database architecture, business intelligence, machine learning, advanced analytics, and big data.
• Strong knowledge of Apache Airflow for workflow orchestration.
• Strong knowledge of CI/CD pipelines and deployment automation for AWS‑based solutions.
• Experience migrating relational databases, Java and Python applications, machine learning model code, and Elasticsearch‑based solutions.
• Experience with Docker and Kubernetes is preferred.
• Curiosity and enthusiasm for learning new technologies, combined with a strong commitment to hands‑on engineering.
• Effective written and verbal communication skills, with the ability to explain technical concepts and collaborate with stakeholders and senior management.
• Ability to perform data and system analysis, identify root causes, and translate findings into actionable recommendations.
• Ability to adapt to changing priorities and work effectively in a collaborative, fast‑paced environment.

Salary Range

$90,000 - $157,500 Annual

The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.

Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long‑term disability, and other optional additional coverages; paid‑time off including vacation, sick leave, short‑term disability, and family care responsibilities; access to our Employee Assistance Program; incentive compensation including eligibility for annual performance‑based awards (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans. For a full overview, visit https://hrportal.ehr.com/statestreet/Home.

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work‑life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

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Job Application Disclosure

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.