Job description

State Street Investment Management Data, Analytics & AI Services (DAAIS) team is We are seeking an experienced Officer‑level Senior Data Engineer (Cloud & Analytics) to join our Boston office. This role is responsible for designing and building modern cloud‑based data engineering solutions that enable analytics, reporting, and AI use cases for Client Coverage Group (CCG) and Chief Business Office (CBO)for Sales and Business teams. The ideal candidate combines solid hands-on engineering fundamentals, system integration experience, and AI-enabled approach to day-to-day execution. The role requires strong ownership of technical components, independence in execution, and close collaboration with cross‑functional stakeholders while operating as a senior individual contributor. Job Description Key Responsibilities & Experience Range Design, develop, and support end‑to‑end data pipelines with AWS, Redshift, Databricks, and Snowflake , ensuring high‑quality, secure, and scalable cloud‑based data platforms. Implement and maintain enterprise system-to-system integrations using APIs, event-based patterns, and secure authentication mechanisms. Build scalable robust data ingestion, transformation, and validation frameworks using Python, SQL, and Shell scripting Develop and optimize data pipelines for performance, reliability, and data quality Partner with product owners, analytics teams, and downstream consumers to translate business requirements into technical solutions Support production stability , incident resolution, and root‑cause analysis for data platforms Actively participate in architecture discussions, design reviews, and technical walkthroughs Follow Agile delivery practices , including sprint planning, estimation, and issue tracking using project collaboration JIRA Ensure compliance with data security, governance, and SDLC standards Apply AI code generation tools (e.g., Anthropic Code, Codex, and GitHub Copilot) to accelerate development, improve quality, and increase productivity. Contribute to structured and unstructured data workflows, leveraging AI technologies. Continuously identify opportunities to improve efficiency, automation, and platform capability Good Analytical skills to understand the business requirements and translate them into Technical specifications Good hands-on to AWS Data storage products like AWS S3 and Amazon Redshift. Ability to participate in major incident management, production stability, etc as and when required Excellent verbal and written communication and should be able to work with all the stakeholders. Prior experience on working in Agile project management practices Qualification & Certifications Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. 6–10 years of overall IT experience, with strong focus on Data Engineering 4 years of hands‑on experience building data pipelines on cloud platforms Proven experience working as a senior data engineer/ETL expert on complex technical problem statements Excellent communication and leadership skills. Primary Skills (Must Have) Proficient on in designing ,developing and supporting AWS-based Data pipelines and cloud architectures with AWS (S3,AWS Redshift, EC2, IAM) with Apache Airflow, YAML, and Shell Scripting. Solid AWS Cloud experience, including S3 , IAM, and cloud‑based data architectures Proficiency in Python for data engineering and automation Strong Python and SQL skills for data engineering analysis, validation, and performance tuning Experience writing and maintaining Shell scripts for automation and operational support Experience working with unstructured data (e.g., Sales note, 13F filings, news, social media). Good understanding of Data Warehousing, Data Lakes, and Data Quality concepts Ability to independently analyze requirements and deliver technical solutions Secondary Skills (Good to Have) Exposure on AWS Cloud Tech Stack for Data Engineering. Good to have hands on Databricks and Snowflake. Experience with Salesforce ecosystem, including Salesforce data model and API-based integration patterns. Exposure to any financial/asset management domain or sales and marketing would be added advantage. Exposure to code versioning tool GIT, Bitbucket and CI/CD Process for Deployment and Releases. Knowledge of networking fundamentals and key management services Good understanding/hands-on of application of AI /ML in data engineering and data quality. Salary Range: $70,000 - $118,750 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 hrportal.ehr.com . 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. Discover more information on jobs at StateStreet.com/careers Read our CEO Statement 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.

Requirements

Must-haves

The role requires strong ownership of technical components, independence in execution, and close collaboration with cross‑functional stakeholders while operating as a senior individual contributor.
Key Responsibilities & Experience Range
Design, develop, and support end‑to‑end data pipelines with AWS, Redshift, Databricks, and Snowflake , ensuring high‑quality, secure, and scalable cloud‑based data platforms.
Implement and maintain enterprise system-to-system integrations using APIs, event-based patterns, and secure authentication mechanisms.
Build scalable robust data ingestion, transformation, and validation frameworks using Python, SQL, and Shell scripting
Develop and optimize data pipelines for performance, reliability, and data quality
Partner with product owners, analytics teams, and downstream consumers to translate business requirements into technical solutions
Support production stability , incident resolution, and root‑cause analysis for data platforms
Actively participate in architecture discussions, design reviews, and technical walkthroughs
Follow Agile delivery practices , including sprint planning, estimation, and issue tracking using project collaboration JIRA
Ensure compliance with data security, governance, and SDLC standards
Apply AI code generation tools (e.g., Anthropic Code, Codex, and GitHub Copilot) to accelerate development, improve quality, and increase productivity.
Contribute to structured and unstructured data workflows, leveraging AI technologies.
Continuously identify opportunities to improve efficiency, automation, and platform capability
Good Analytical skills to understand the business requirements and translate them into Technical specifications
Good hands-on to AWS Data storage products like AWS S3 and Amazon Redshift.
Ability to participate in major incident management, production stability, etc as and when required
Excellent verbal and written communication and should be able to work with all the stakeholders.
Prior experience on working in Agile project management practices
Qualification & Certifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
6–10 years of overall IT experience, with strong focus on Data Engineering
4 years of hands‑on experience building data pipelines on cloud platforms
Proven experience working as a senior data engineer/ETL expert on complex technical problem statements

Nice-to-haves

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Application prep

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Keywords to mirror

aiawspythonsqlagilejiraapici/cdml

Platform: workday
Effort: long

Benefits

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Dental

Vision

401k