Data Architect

Location: New York City, NY, onsite (local candidates are a top priority). Duration: 12+ months, 40 hours a week.

About the role

We are seeking a highly experienced Senior Data Architect with strong hands-on expertise in data analytics, Databricks on AWS, PySpark, Python, SQL, and ETL tools such as Informatica. This is a senior leadership role requiring strong technical ownership, proactive risk and issue management, and excellent communication skills. The ideal candidate will have deep experience designing scalable, secure, and cost-efficient data solutions on AWS, migrating data assets from on-premises platforms to the cloud, and leveraging GenAI-driven automation to accelerate data modernization initiatives.

Responsibilities

• Design and implement scalable, secure, and cost-efficient data architecture solutions on AWS.
• Lead data migration initiatives from on-premises environments to AWS.
• Work hands-on with Databricks on AWS, PySpark, Python, and SQL to build data pipelines and analytical solutions.
• Develop data models and deliver data-driven insights to support business decision-making.
• Design and build PySpark applications to extract, transform, aggregate, and analyze large datasets.
• Support migration of data assets to the cloud using GenAI-enabled automation approaches.
• Work with large language models including pretraining, fine-tuning, augmentation, and optimization use cases where applicable.
• Identify, gather, and consolidate data from diverse sources including internal databases, spreadsheets, and enterprise systems.
• Apply data quality checks, cleaning processes, and transformations using Python, Pandas, and SQL.
• Automate repetitive data preparation and workflow tasks using scalable scripts and code-based practices.
• Collaborate with stakeholders to clarify requirements, challenge assumptions, and validate data quality.
• Document data workflows, coding standards, analytical methodologies, and best practices.
• Proactively identify, communicate, and manage project risks, issues, dependencies, and delivery blockers.
• Operate independently with minimal supervision while maintaining strong collaboration with business and technical teams.

Requirements

• 15+ years of experience as a Data Architect, Data Engineer, Data Analyst, or related data-focused role.
• Hands-on experience with Databricks on AWS.
• Strong PySpark, Python, Pandas, SQL, and data analytics experience.
• Experience with ETL tools such as Informatica.
• Proven experience migrating data from on-premises platforms to AWS.
• Experience designing and implementing scalable, secure, and cost-efficient data solutions on AWS.
• Strong data modeling and database solution design experience.
• Experience developing PySpark applications for extraction, transformation, aggregation, and insight generation.
• Experience with GenAI-driven automation for cloud data migration or data modernization.
• Exposure to LLM pretraining, fine-tuning, augmentation, and optimization.
• Ability to automate data workflows and implement code-based best practices.
• Strong documentation, communication, stakeholder engagement, and requirement clarification skills.

Preferred Qualifications

• Experience with Python libraries such as Pandas, Scikit-learn, and Matplotlib.
• Experience working with multiple structured and semi-structured data formats.
• Strong understanding of data governance, data quality, and reproducibility practices.
• Experience in large enterprise data modernization programs.
• Bachelor's degree or higher in Computer Science, Data Engineering, Analytics, or a related field.

Behavioral Expectations

• Excellent communication skills with the ability to explain analytical findings to technical and non-technical stakeholders.
• Proactive approach to risk and issue management.
• Strong critical thinking and problem-solving ability.
• Ability to question assumptions, assess data quality, and recommend alternative approaches.
• Self-directed, resourceful, and comfortable managing priorities independently.
• Collaborative mindset with the ability to work closely with cross-functional teams.