Top Data Architect Jobs in NYC, NY

As a Senior Manager in Data and Analytics Engineering at PwC, you'll design data architecture strategies for healthcare, mentor teams, influence stakeholders, and enhance healthcare operations through data solutions.

Design and implement data management strategies, creating scalable data solutions, and collaborating with teams to address business challenges and ensure data integrity.

The Staff Data Architect will enhance Jellyfish's data platform through architectural design, automation, advanced observability, and efficient data governance, while collaborating across teams.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.

The Data Architect will utilize data modeling tools, design data lakes, and ensure proper tuning of NoSQL models while managing object design and deployment scripting.

The role involves reverse engineering and optimizing complex database environments, analyzing database schemas, designing data models for efficiency, and administering enterprise databases.

The role encompasses leading the architecture and modernization of enterprise data structures, focusing on data governance, integration, and cloud platforms, while collaborating with different business units to enhance data usability and analytics.

Lead enterprise data architecture, design cloud data warehouse/lakehouse solutions (Snowflake, Databricks), define modeling and governance, build integrations and APIs, support implementations, ensure data quality, and advise on LLM/RAG and vector embedding infrastructure for financial services.

Design and govern Axiom's enterprise data model, establish data governance and quality standards, manage a Data Engineer, align data architecture roadmap with enterprise strategy, administer Databricks, enable AI data access (MCP), and liaison with Product, Operations, and Data Science to ensure accessible, documented, and reliable data assets.

The Data Architect will design and evolve the architecture for the Consumer Canvas platform, ensuring data scalability, security, and privacy. Responsibilities include managing data ingestion, PII governance, and collaborating with cross-functional teams to develop and implement innovative data solutions.

Design and govern enterprise data architectures within the Informatica ecosystem. Lead data modeling, ETL/integration using Informatica tools, enforce data quality and governance, optimize performance, manage metadata and lineage, collaborate with stakeholders, document solutions, and train teams.

The Sr. Manager of Data Engineering & Analytics will define data strategy, oversee a data team, and build scalable data platforms, ensuring data quality and governance.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

As a Data Architect II, you will design and deliver data products, develop data models, and guide architecture decisions to enhance member journey analytics and reporting at Hagerty.

The Salesforce Data Architect will lead complex data migration initiatives, ensuring data quality and governance while collaborating with stakeholders to implement scalable Salesforce solutions.

Lead design and execution of data migration strategies for Salesforce Revenue Cloud (CPQ & Billing). Define data architecture, mappings, and transformation logic; build SQL-based extraction and ETL processes; perform iterative test loads, reconciliation, and validation. Collaborate with clients and cross-functional teams to manage cutovers, documentation, and migration quality for quote-to-cash data.

The Principal Data Architect will design and oversee the enterprise data architecture, ensuring effective modeling, integration, governance, and consumption of data across the organization. Responsibilities include building data models, implementing lakehouse strategies, and partnering with multiple teams for the evolution of data practices.

Lead ER/Studio data architecture and modeling efforts: build/maintain macros, standardize domains and metadata, synchronize models with physical databases, enforce naming/versioning standards, document and support modelers and DB engineering for BI and data integration.

Design and develop scalable big-data solutions using Hadoop ecosystem technologies. Lead requirements gathering, implement Spark/MapReduce workflows, integrate NoSQL databases, mentor team members, and collaborate with stakeholders to solve complex data problems.

Design, gather requirements for, and develop scalable Hadoop-based big data solutions. Work with Hadoop ecosystem and NoSQL databases, implement Spark/MapReduce jobs, and use Hive, Sqoop, Oozie, Flume and programming languages (Java/Scala/Python). Mentor team members, solve analytical problems, and learn business domain. R experience desirable.

Design and implement data lake ingestion and client consumption solutions. Work with Hadoop (HDFS, YARN), optimize Hive, build Spark jobs (Python/Scala), use Informatica PowerCenter, and deploy/operate solutions on AWS while meeting deadlines and leading tasks.

Design, build, and support data lake/data management, ingestion, and client consumption. Require strong Big Data fundamentals (HDFS, YARN, Hive tuning), solid Spark (Python/Scala) skills, AWS cloud experience, ETL tooling (Informatica) knowledge, and familiarity with NoSQL tools like Cassandra, Drill, and Impala.

Design, build, and support a data lake: manage ingestion, data management, and client consumption. Implement Big Data platforms (HDFS, YARN), optimize Hive (partitioning, reducer/block sizing), develop Spark jobs (Python/Scala), work with ETL tools (Informatica) and NoSQL (Cassandra, Drill, Impala) in AWS. Meet deadlines, handle multiple tasks, and communicate with stakeholders.

The Senior Data Architect will design and lead the architecture of Trexquant's data ecosystem, ensuring unified access and efficiency by creating intuitive data solutions for researchers and simulators across various asset classes.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.