Data Engineer - Cloud & Analytics, Officer - State Street Investment Management

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 Git Hub 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…