Top Data Architect Jobs in NYC, NY

Lead the data team in building a data vault and warehouse on Snowflake, manage tasks, and ensure quality data through sprint cycles.

The Data Architect will shape the data architecture and reporting strategy, ensuring data governance and developing scalable data solutions on Azure services.

Lead design and evolution of a cloud-native Snowflake data platform using medallion/lakehouse patterns. Implement governance, security, ingestion integrations, cost forecasting, and observability. Collaborate with Azure teams, mentor engineers, and translate architectural trade-offs for stakeholders while championing AI adoption.

Senior, hands-on role defining enterprise data architecture and standards across cloud platforms (Snowflake, Databricks, Azure). Design data models, integration patterns, governance, and pipelines to support analytics and AI/ML. Lead platform decisions, ensure security, metadata, and MDM; mentor teams and drive architecture reviews and documentation.

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.

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.

Design, implement, and optimize enterprise data architecture and management for healthcare analytics. Lead data solutions using Microsoft Fabric and Power BI, ensure data governance, integrate imaging and EMR systems, troubleshoot ETL/SSIS, manage projects, mentor staff, and ensure HIPAA-compliant 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.

Design, implement, and maintain Hadoop-based big data platforms using HDFS, Pig, Hive, HBase and Sqoop. Lead and provide oversight to the Hadoop team, write/debug Pig/Hive/Sqoop and shell/Python code, perform performance tuning and troubleshooting, liaise with application teams for issue resolution, and provide on-call weekend support.

Lead design and delivery of an enterprise data platform covering ingestion, storage, processing, governance, and consumption. Define architecture standards, drive lakehouse/warehouse/streaming solutions, integrate governance and security, optimize cost and capacity, mentor engineers, and produce architecture artifacts to support ML, BI, and product teams.

Design, implement, and maintain MOCJ's data architecture including data models, warehouses, lakes, and ETL/ELT pipelines. Ensure data integration, quality, governance, security, and compliance; recommend platforms and cloud solutions; optimize performance and support cross-functional teams to translate business needs into scalable data solutions.

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

Design and own data migration strategy and architecture. Map source-to-target data models, build data dictionaries, perform migrations and testing, reconcile results, and collaborate with stakeholders and project teams to ensure successful modernization.

Lead design and implementation of scalable data architectures using Capsenta. Build and maintain data models, ontologies, and graph databases; manage databases; integrate data sources; optimize performance; enforce data governance; document solutions; collaborate with engineers and stakeholders; and stay current on semantic and knowledge-graph technologies.

Design scalable, secure data architectures on Google Cloud, lead discovery and migration from legacy systems, define ETL/ELT patterns, enforce governance and security, optimize performance, collaborate with stakeholders, and document architecture and migration progress.

Design, build, and optimize Spark ETL pipelines using Scala/Python and Oracle SQL. Lead and mentor a team of engineers, collaborate with stakeholders on scalable data solutions, ensure data integrity, security, and performance, and stay current on emerging technologies to drive improvements.