Data Architect

Job Description

As a Data Architect at Acumatica, you will have the opportunity to envision, design, implement and operate a state-of-the-art data platform, Lakehouse infrastructure, data pipelines, and associated processes.

The ideal candidate will have a strong background in the creation of scalable, unified architectures to support both real-time and batch analytics & machine learning, ensuring seamless data integration, governance, and accessibility.

Responsibilities

• Architect a robust data platform and ecosystem of technology, combining structured and unstructured data storage with analytical processing.
• Define strategies and develop data pipelines for ingestion, transformation, and optimization within the lakehouse.
• Establish policies for data governance quality, privacy, and security in compliance with global regulations like GDPR, PCI, HIPAA and CCPA.
• Assert data governance principles and evangelize company wide.
• Ensure secure data access and robust role-based permissions.
• Leverage tools like Delta Lake & Apache Iceberg for Lakehouse architecture.
• Make recommendations for improvements considering cost and time to value.
• Monitor & enhance query performance, storage costs, and system scalability.
• Enable self-service analytics and facilitate efficient data exploration.
• Partner with IT, Analytics, Business & Engineering teams to align data strategies.
• Lead cross-functional projects, mentoring engineers on modern data architectures.
• Regularly present proposals to cross functional audiences, like the Architectural Review Board, to drive cross-functional alignment of ideas and support.
• Establish enterprise data service performance standards and SLAs.

Qualifications

• 8+ years in data architecture & engineering with expertise in data lakehouse or modern data architecture.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• Expertise in designing & managing big data platforms, data warehouses/lakehouses or similar hybrid architectures.
• Ability to be a technical lead for a team of 3-5 data engineers.
• Strong skills in SQL, Python, Java, and cloud native tools for data storage & analytics.
• Strong data modeling experience.
• Strong knowledge of ETL/ELT pipelines, streaming data, and orchestration frameworks.
• Understanding of data governance frameworks & compliance standards.
• Experience integrating machine learning workflows into lakehouse environments.
• Prefer experience with database performance testing and SQL optimization.
• Excellent communication & collaboration abilities with remote team members.
• Excellent documentation skills for writing policies, defining business metrics/data glossary terms, writing proposals, and detailing architectures.
• Ability to articulate vision & strategy to senior leadership.

Additional Information

Work Perks:

• Industry competitive salary
• Comprehensive Health & Life insurances
• Hybrid working
• Office lunch
• Exposure to working with distributed global teams
• Paid paternity leave

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