Top Data Architect Jobs in NYC, NY

Lead design, implementation, and operation of a scalable, secure cloud data platform (data lake/warehouse/lakehouse). Build data pipelines, migrations, archival, IaC provisioning, CDC-enabled ingestion, governance, multi-tenant security, DR/HA, and performance optimization to support reporting, analytics, and AI/ML for a federal judiciary modernization program.

Lead enterprise data architecture across multiple SaaS products by unifying reporting platforms, data models, and analytics capabilities. Assess current systems, define target-state architecture, establish data governance and quality standards, separate analytical workloads from transactional systems, and develop phased migration roadmaps. Guide database, engineering, and BI teams on cloud platforms, integration, modeling, performance, security, and reliability. Enable trusted cross-product reporting, governed self-service analytics, and data foundations for AI and advanced analytics.

Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.

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 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 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.

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, 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 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.

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.

Serve as a senior advisor on enterprise data architecture and Adobe Experience Platform. Lead client discovery, design XDM schemas and identity resolution, guide data ingestion/ETL, governance, and Customer 360 initiatives. Provide technical leadership, mentor teams, review architecture, and contribute templates and best practices across consulting engagements.

Design and implement enterprise data architecture and ETL/ELT on GCP (BigQuery). Own ingestion, transformation, modeling, orchestration, governance, and platform roadmap. Collaborate with business and BI teams, mentor engineers, drive modernization (lakehouse, data mesh, streaming), and ensure scalable, secure, high-performance data products for analytics.

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

Lead architect to design and implement large-scale, distributed big data solutions using Java and Big Data technologies. Hands-on with Java 1.8+, Apache Spark, MapReduce, Hadoop/Cloudera, Hive, Impala, YARN, and Kafka. Perform data analysis, design scalable architectures, enforce testing (JUnit), and optionally use Unix/Python scripting. Manage global technology teams, apply industry best practices, and communicate effectively across stakeholders.

Design and implement scalable end-to-end data architectures, including data modeling, ETL/ELT pipelines, cloud data platforms, streaming integrations, governance, security, and enablement for analytics and AI/ML. Mentor engineers and document architecture for stakeholders.

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.

Lead database design, data modeling, schema evolution, migrations, and ETL/ELT pipelines across MySQL, PostgreSQL, and Google Cloud databases. Build streaming and batch ingestion, enable CI/CD for data deployments, troubleshoot pipelines, produce runbooks, and mentor/lead offshore DB/ETL engineers while collaborating with onshore architects.

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, 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.

Design and operationalize FHIR-compliant data models and scalable integration solutions to harmonize EHR, HIE, and claims data. Build validation frameworks and automated rules to ensure clinical accuracy and longitudinal integrity. Produce clear documentation and collaborate with engineering and cross-functional teams to support analytics, operational, and research initiatives.

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.

Lead enterprise data architecture on Snowflake, define Medallion Architecture and data modeling standards, guide dbt/Python pipeline frameworks, enforce HIPAA-compliant governance, optimize performance and cost, and mentor engineers while collaborating with analytics, clinical, and product stakeholders.

Lead definition and evolution of cloud data architecture and analytics platform using a lakehouse approach. Design secure, scalable AWS data platforms, medallion data layers, data modeling standards, ETL/ELT and streaming pipelines, governance, observability, and AI/ML enablement. Drive tool selection, cross-team architecture reviews, mentor engineers, and enforce data security, compliance, and operational excellence across the organization.

The Data Architect/Data Governance Lead supports the Medicaid Enterprise Data Warehouse by leading data architecture, metadata management, and governance processes, ensuring compliance and scalability.

Design, architect, and implement scalable high-performance big data solutions on Hadoop ecosystems. Lead workshops, produce proposals and technical documentation, perform reviews, profiling, troubleshooting, cluster sizing, and deploy clustered solutions. Mentor senior leaders and contribute to open-source integrations.