Data Engineering Lead, Avp

State Street Corporation

Not specified
Design, build, and operation of analytical data products
End-to-end delivery of batch and streaming data pipelines
Curated lakehouse datasets
State Street Corporation is seeking a Data Engineering Lead, AVP, to oversee the design and operation of analytical data products on their xData Platform. The role requires strong technical expertise in data engineering and a focus on building scalable data solutions while fostering a collaborative environment

Job Summary

  • Lead the design, build, and operation of trusted analytical data products on the Target State xData Platform.
  • Own end‑to‑end delivery of complex batch and streaming data pipelines, curated Lakehouse datasets, and analytics‑ready models supporting Core Reference Data, Security Master, IBOR Holdings & Transactions, Datahub, Stamford Data Warehouse, and many other data initiatives.
  • Partner closely with Platform Engineering and Data Platform Architecture to deliver scalable, governed, and production grade data solutions.

Matching Summary

Match Score: 85

State Street Corporation is seeking a Data Engineering Lead, AVP, to oversee the design and operation of analytical data products on their xData Platform. The role requires strong technical expertise in data engineering and a focus on building scalable data solutions while fostering a collaborative environment.

Skills & Requirements

Must-have

  • design, build, and operation of analytical data products
  • end-to-end delivery of batch and streaming data pipelines
  • curated Lakehouse datasets
  • analytics-ready models
  • Databricks, Snowflake, Spark, Informatica ETL
  • Iceberg-based lakehouse tables
  • define and enforce engineering standards
  • logical and physical data modeling
  • define data semantics, stewardship expectations
  • implementation of data quality rules
  • review designs and code
  • CI/CD adoption, deployment standardization
  • production stability for data products
  • incident management, root cause analysis
  • mentor and guide data engineers

Nice-to-have

  • financial or enterprise data platform background

Key Requirements

  • Strong hands-on data engineering experience with Python, Java, and SQL
  • Advanced expertise in Spark and SQL
  • Hands-on experience with Snowflake and Databricks
  • Deep working knowledge of Apache Iceberg
  • Strong understanding of distributed data processing
  • Experience building and operating production grade data pipelines in AWS, Azure, and/or GCP
  • Solid understanding of curated analytical models and data product design
  • Experience with CI/CD, automated testing, and production support practices

Work Rights

Not specified

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