
Leading company in the financial services industry
Senior Data Engineer - Manager
Officer – Data Platform Engineering Role Summary
State Street Investment Management’s Data, Analytics & AI Services (DAAIS) team is seeking a Senior Data Engineer (Officer) for our Bangalore, India office. This role is accountable for building and operating modern data platform and data pipeline capabilities that enable the investment management business. The successful candidate will bring strong hands-on expertise in distributed data processing, data pipeline engineering, and cloud-based data platforms. The role will execute on solutions and technical direction defined by platform leadership/architecture, with a focus on reliable delivery, day-to-day operations, and continuous improvement of production data workloads.
Key Responsibilities
- Build and operate end-to-end batch and streaming data pipelines on lakehouse platforms (Snowflake/Databricks, Apache Spark), delivering curated, analytics-ready datasets aligned to established standards.
- Develop production-grade pipeline code using Python, Java/Scala, and SQL, applying best practices for reliability, maintainability, performance, and testability.
- Implement and maintain Apache Iceberg tables based on defined patterns, including partitioning, schema evolution, and metadata/catalog practices to support efficient analytical access.
- Deliver governed data integration and curation for reference and application domains; publish semantic/serving models via BI tools and other approved consumption interfaces.
- Implement automated data quality, validation, reconciliation, lineage, and observability to ensure trusted, auditable, production-grade outcomes.
- Partner with domain SMEs, architects, and application teams to understand data requirements and semantics, and implement agreed logical/physical models and consumption contracts.
- Use standard CI/CD pipelines and platform tooling to deploy and run data workloads; follow platform guardrails, security requirements, and operational best practices.
- Maintain data product interfaces (schemas, SLAs, documentation, versioning, and lifecycle processes) in alignment with the broader platform standards.
- Troubleshoot data and environment issues through impact analysis, root-cause analysis, and corrective/preventive actions; document fixes and lessons learned.
- Support incident management, execute backfills as needed, and maintain production stability for data pipelines.
Required Qualifications
- 10+ years of experience in software and/or data engineering; BS/MS in Computer Science, Engineering, or equivalent practical experience.
- Strong programming skills in Python and SQL; Java/Scala experience preferred; ability to write production-quality, well-tested, maintainable code.
- Hands-on experience with Apache Spark (batch and/or streaming), including troubleshooting, performance tuning, and cost-aware optimization.
- Hands-on experience with Snowflake and Databricks in an enterprise environment, including job orchestration, query optimization, and platform operations.
- Experience building production-grade data pipelines in cloud environments (AWS preferred; GCP or Azure acceptable).
- Solid understanding of data modeling concepts, ETL/ELT patterns, schema evolution, and distributed data processing principles across structured and unstructured data.
- Working knowledge of lakehouse/data platform components (e.g., Databricks, Snowflake, Trino, Iceberg) and interoperability, connectivity, and access patterns.
- Working knowledge of open table formats and metadata/catalog ecosystems (e.g., Apache Iceberg; Unity Catalog or equivalent).
- Experience in Capital Markets, with understanding of key reference/application domains (e.g., Securities, Benchmarking, Holdings, Sales, Accounts, Products).
- Excellent written and verbal communication skills, with demonstrated ability to collaborate with global engineering, operations, and business stakeholders.
Preferred Qualifications
- Experience with data quality frameworks, automated reconciliation patterns, and data lineage tooling.
- Professional Certificates on Snowflake and/or Databricks
Professional Certificates on AWS, GCP and/or Azure
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
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关于State Street

State Street
PublicState Street Corporation is an American multinational financial services and bank holding company headquartered at One Congress Street in Boston. It is the second-oldest continuously operating U.S. bank, tracing its roots to Union Bank, chartered in 1792.
10,001+
员工数
Boston
总部位置
$55B
企业估值
评价
10条评价
3.7
10条评价
工作生活平衡
3.2
薪酬
4.0
企业文化
3.8
职业发展
3.4
管理层
2.8
68%
推荐率
优点
Supportive colleagues and team culture
Good benefits and retirement plans
Learning and advancement opportunities
缺点
Heavy workload and overtime expectations
Poor management direction and support
High stress and fast-paced environment
薪资范围
101个数据点
Junior/L3
Mid/L4
Junior/L3 · Business Analyst
2份报告
$134,560
年薪总额
基本工资
$117,009
股票
-
奖金
-
$127,061
$142,060
面试评价
5条评价
难度
2.6
/ 5
时长
21-35周
录用率
20%
体验
正面 20%
中性 60%
负面 20%
面试流程
1
Application Review
2
Recruiter Screen
3
Phone Interview
4
Technical/Hiring Manager Interview
5
Final Interview/Offer Stage
常见问题
Technical Knowledge
Behavioral/STAR
Past Experience
Culture Fit
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