Data Architect

Summary

Join Later as a Data Architect and design, manage, and implement the organization's data architecture. You will develop and implement a comprehensive data architecture strategy, integrate data from various sources, and build scalable data solutions. Collaborate with various teams to ensure data needs are met and align with business objectives. The ideal candidate possesses extensive experience in data architecture, data engineering, and related fields, along with proficiency in data modeling, ETL processes, and database technologies. A strong technical background and understanding of both traditional and modern data architectures are essential. Later offers a competitive salary and benefits package.

Requirements

• 7+ years in data architecture, data engineering, or a related field, with proven experience designing data solutions for large-scale applications
• Bachelor’s degree in Computer Science, Information Systems, or a related field (Master’s preferred)
• Proficiency in data modeling, ETL processes, and database technologies (SQL/NoSQL), as well as data warehousing solutions (e.g., Snowflake, Redshift, BigQuery)
• Hands-on experience with cloud data platforms (e.g., AWS, Azure, Google Cloud) and associated tools (e.g., Glue, Dataflow)
• Knowledge of big data processing frameworks (e.g., Hadoop, Spark) and experience with real-time data processing and streaming (e.g., Kafka)
• Experience in designing and managing data warehouses, data lakes, and real-time data pipelines
• Deep understanding of data governance principles, including data quality management, metadata management, and master data management (MDM)
• Strong analytical skills with a focus on translating complex requirements into scalable solutions
• Strong documentation skills to maintain detailed technical documentation for data architecture, including design specifications and best practices
• Ability to work effectively with both technical and non-technical stakeholders and articulate data architecture concepts clearly, including the ability to influence and drive data architecture best practices across the organization
• Experience in implementing data security measures and ensuring compliance with regulatory requirements (e.g., GDPR, CCPA)
• Ability to stay updated on emerging data technologies and industry trends, and incorporate new knowledge into architectural practices

Responsibilities

• Develop and implement a comprehensive data architecture strategy, including data modeling, data integration, and data storage solutions to support current and future needs
• Lead efforts to integrate data from various sources, ensuring seamless data flow and consistency across different systems and platforms
• Design and maintain scalable data solutions, including data lakes, data warehouses, and real-time data pipelines that enable efficient data processing and accessibility
• Collaborate with BI and analytics teams to design and implement data visualization solutions that provide actionable insights
• Establish and enforce data governance policies to ensure data quality, consistency, security, and compliance with regulatory requirements
• Work closely with data engineering, analytics, and business teams to understand data needs and ensure alignment of data architecture with business objectives
• Evaluate and recommend new data technologies, frameworks, and tools to improve data capabilities and operational efficiency
• Define and document data standards, architectural designs, and best practices to create a cohesive data ecosystem
• Implement processes and tools to continuously monitor and improve data quality, addressing issues such as data accuracy, completeness, and timeliness
• Implement security protocols and privacy best practices to protect sensitive data and ensure compliance with privacy regulations (e.g., GDPR, CCPA)
• Oversee the lifecycle of data from creation to archiving, ensuring efficient data retention, retrieval, and deletion practices
• Implement MDM strategies to ensure a single, consistent, and accurate view of critical business data across the organization
• Establish and maintain a metadata repository to enable better data discovery, governance, and usage

Preferred Qualifications

• Master’s degree in Computer Science, Information Systems, or a related field
• Familiarity with machine learning pipelines and supporting data infrastructure
• Knowledge of agile methodologies and data management best practices

Benefits

• Stock options
• Various benefits plans
• Salary Range: $130,000 - $160,000