Senior Director, Data Architect

Jobtailor; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor is seeking a Data Platform Engineer to design, build, and sustain enterprise-scale data products and platforms. You will deliver reliable software across batch, near-real-time, and event-driven patterns, applying discipline in testing, observability, and documentation.

You will help evolve a large-scale data platform, implement scalable ingestion, transformation, and storage patterns, and drive modernization across teams while aligning with security and governance standards.

Qualifications

• Bachelor’s degree or equivalent practical experience in a relevant field.
• Significant experience in data engineering, software engineering, or data platform engineering.
• Proven ability to deliver enterprise-scale data and software solutions in complex environments.
• Strong hands-on experience with modern data technologies.
• Strong proficiency in Python, SQL, and at least one additional language such as Java or Scala.
• Experience with distributed data processing and pipeline design using modern frameworks and tooling.
• Experience with DevOps and software delivery practices including CI/CD, version control, automated testing, and infrastructure automation.
• Strong understanding of data architecture, data modeling, large-scale systems design, and platform engineering concepts.
• Demonstrated ability to influence technical decisions across teams and functions.
• Strong communication and stakeholder management skills.

Responsibilities

• Design, build, test, deploy, and support high-quality data products and platform capabilities for enterprise use cases.
• Deliver scalable and reliable software solutions across batch, near-real-time, and event-driven data patterns, as needed.
• Apply strong software engineering discipline, including code quality, automated testing, CI/CD, observability, and documentation.
• Drive engineering excellence across the delivery lifecycle, with a focus on stability, maintainability, performance, and reuse.
• Ensure data solutions are production-ready and aligned to enterprise standards for security, resiliency, and operational support.
• Build modern data products that are consumable, well-governed, and aligned to business and platform objectives.
• Contribute to the design and evolution of a large-scale, multi-business data platform supporting diverse data domains and consumption models.
• Define and implement scalable patterns for ingestion, transformation, storage, metadata, lineage, access management, and delivery.
• Develop reusable services, frameworks, and engineering patterns that accelerate delivery across teams.
• Support cloud and hybrid data architectures using modern storage and compute approaches.
• Architect enterprise-scale data capabilities leveraging Snowflake, Apache Iceberg, Oracle Exadata, Azure, and other relevant technologies.
• Evaluate current-state architecture, identify opportunities for simplification and modernization, and recommend target-state solutions.
• Make sound design decisions that balance business outcomes, risk management, scalability, cost, and speed of execution.
• Contribute to enterprise engineering standards, architecture patterns, and platform guardrails.
• Lead through technical depth, strong judgment, and the ability to convert strategy into practical engineering outcomes.
• Translate business priorities and platform strategy into actionable technical roadmaps and delivery plans.
• Partner with product, architecture, infrastructure, security, governance, and business stakeholders to align on priorities and sequencing.
• Influence decisions across the broader organization through strong communication, partnership, and credibility.
• Identify and address technical debt, platform gaps, and delivery risks in a proactive and structured way.
• Contribute to longer-term platform strategy while ensuring strong near-term execution against commitments.
• Work effectively across a matrixed organization and multiple lines of business.
• Build strong relationships with engineering teams, platform teams, architects, and business partners.
• Communicate complex technical topics clearly to both technical and non-technical stakeholders.
• Mentor team members and help elevate engineering and delivery practices across the organization.
• Demonstrate ownership, accountability, curiosity, and a strong bias for execution.

Skills

Python

SQL

Java or Scala

CI/CD

Data modeling

Distributed data processing

DevOps practices

Stakeholder management

Communication

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field

Job description

Responsibilities

• Design, build, test, deploy, and support high-quality data products and platform capabilities for enterprise use cases.
• Deliver scalable and reliable software solutions across batch, near-real-time, and event-driven data patterns, as needed.
• Apply strong software engineering discipline, including code quality, automated testing, CI/CD, observability, and documentation.
• Drive engineering excellence across the delivery lifecycle, with a focus on stability, maintainability, performance, and reuse.
• Ensure data solutions are production-ready and aligned to enterprise standards for security, resiliency, and operational support.
• Build modern data products that are consumable, well-governed, and aligned to business and platform objectives.
• Contribute to the design and evolution of a large-scale, multi-business data platform supporting diverse data domains and consumption models.
• Define and implement scalable patterns for ingestion, transformation, storage, metadata, lineage, access management, and delivery.
• Develop reusable services, frameworks, and engineering patterns that accelerate delivery across teams.
• Support cloud and hybrid data architectures using modern storage and compute approaches.
• Architect enterprise-scale data capabilities leveraging Snowflake, Apache Iceberg, Oracle Exadata, Azure, and other relevant technologies.
• Evaluate current-state architecture, identify opportunities for simplification and modernization, and recommend target-state solutions.
• Make sound design decisions that balance business outcomes, risk management, scalability, cost, and speed of execution.
• Contribute to enterprise engineering standards, architecture patterns, and platform guardrails.
• Lead through technical depth, strong judgment, and the ability to convert strategy into practical engineering outcomes.
• Translate business priorities and platform strategy into actionable technical roadmaps and delivery plans.
• Partner with product, architecture, infrastructure, security, governance, and business stakeholders to align on priorities and sequencing.
• Influence decisions across the broader organization through strong communication, partnership, and credibility.
• Identify and address technical debt, platform gaps, and delivery risks in a proactive and structured way.
• Contribute to longer-term platform strategy while ensuring strong near-term execution against commitments.
• Work effectively across a matrixed organization and multiple lines of business.
• Build strong relationships with engineering teams, platform teams, architects, and business partners.
• Communicate complex technical topics clearly to both technical and non-technical stakeholders.
• Mentor team members and help elevate engineering and delivery practices across the organization.
• Demonstrate ownership, accountability, curiosity, and a strong bias for execution.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent practical experience.
• Significant experience in data engineering, software engineering, or data platform engineering.
• Proven ability to deliver enterprise-scale data and software solutions in complex environments.
• Strong hands‑on experience with modern data technologies.
• Strong proficiency in Python, SQL, and at least one additional language such as Java or Scala.
• Experience with distributed data processing and pipeline design using modern frameworks and tooling.
• Experience with DevOps and software delivery practices including CI/CD, version control, automated testing, and infrastructure automation.
• Strong understanding of data architecture, data modeling, large‑scale systems design, and platform engineering concepts.
• Demonstrated ability to influence technical decisions across teams and functions.
• Strong communication and stakeholder management skills.

Core Competencies

Demonstrates expertise in designing and delivering enterprise‑scale data products and platforms, with a strong focus on data architecture, software engineering practices, and stakeholder collaboration. Proficient in modern data technologies and methodologies, ensuring solutions are scalable, reliable, and aligned with business objectives.