T26-9768;Software Engineering & Development, VP

Who we are looking for   ONSITE: Due to the role requirements this job needs to be performed primarily in the office with some flex work opportunities available.   As a Data Engineer Lead, you will be responsible for developing, maintaining, and optimizing data pipelines and systems that support the acquisition, storage, transformation, and analysis of large volumes of data. You will collaborate with cross-functional teams, including analysts, software engineers, and operations teams to ensure the availability, reliability, and integrity of data for various business needs. This role requires strong technical expertise in data engineering principles, database management, and programming skills.   We are looking for candidate with good knowledge on Bigdata technology and strong development experience with Snowflake and Databricks. You will help to migrate existing on-prem applications to cloud (Azure preferred), create and maintain new data applications relying on experience and judgment to plan and accomplish goals, while working with other globally situated team members.   What you will be responsible for   As Data Engineer Lead you will   Design, develop, and maintain data pipelines in Azure for ingesting, transforming, and loading data from various sources into centralized Azure data lakes and Databricks Delta Lake and Snowflake as the Data Warehouse. Ensure data quality and integrity throughout the process.   Implement efficient ELT/ETL processes to ensure data quality, consistency, and reliability. Develop transformation processes to clean, aggregate, and enrich raw data, ensuring it is in the appropriate format for downstream analysis and consumption. Integrate data from diverse sources to provide a unified view of information.   Design and implement efficient data models and database schemas that support the storage and retrieval of structured and unstructured data. Optimize data storage and access for performance and scalability.   Implement knowledge of modern data processing principles to streamline data import/transformation processes. Leverage modern data pipeline tools to reduce human attention during ETL process. Ensure the efficiency and reliability of data ingestion and processing.   Integrate with other State Street systems including on cross systems access and implement appropriate entitlement solutions including RBAC and ABAC.   Work closely with cross-functional teams to understand data requirements and translate them into technical solutions.   Monitor data pipelines, troubleshoot issues, and ensure data integrity and security.   Implement data quality controls and validation processes to identify and rectify data anomalies, inconsistencies, and errors. Collaborate with stakeholders to define and enforce data governance standards and policies.   Identify performance bottlenecks in data pipelines and database systems and optimize queries, data structures, and infrastructure configurations to improve overall system performance and scalability.   Implement appropriate security measures to protect sensitive data and ensure compliance with data privacy regulations. Monitor and address data security vulnerabilities and risks.   Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and deliver effective data solutions. Document data engineering processes, data flows, and system configurations.   Stay updated with the latest trends, tools, and technologies in the field of data engineering. Proactively identify opportunities to improve data engineering practices and contribute to the evolution of data infrastructure.   Provide support to the development team with managing multiple instances of databases and servers, implementing complex queries with proper tuning, provide input to design impacting data, manage data infrastructure in Azure ( DataLake , DataWarehouse and Synapse).

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