Data Architect

Role Overview

At NeST Digital, we foster a dynamic environment where professionals can learn, grow and innovate. We are seeking an accomplished and visionary Lead Full Stack Digital Data Architect with 12+ years of extensive experience to join our leadership team. In this highly influential role, you will be responsible for defining and evolving the data strategy, architecture, and governance framework to support our digital initiatives and business objectives. You will bridge the gap between business strategy and technical execution, drive innovation, mentor senior engineers, and ensure our systems are scalable, secure, and future-proof. You will collaborate with cross-functional teams to design and implement data solutions - Develop and maintain data models, data dictionaries, and data flow diagrams.

This individual will define the data requirements and structure for the application, model and design the application data structure, storage, and integration. You will play a crucial role in shaping the data architecture of the organization and ensuring seamless data flow. This role requires a deep understanding of modern data platforms, data integration techniques, data modeling, and data governance best practices. The Digital Data Architect needs to work closely with business stakeholders, IT teams, and data scientists to design scalable, secure, and high-performance data solutions that enable advanced analytics, machine learning, and informed decision-making. This position demands a proactive and results oriented individual with a passion for technology and a commitment to excellence.

Key Responsibilities:

• Design and implement scalable, robust, and secure data solutions across various platforms (e.g., cloud, on premise, hybrid).
• Define, Design and Develop conceptual, logical, and physical data models which are optimized for performance, scalability, and maintainability.
• Collaborate with application development teams to ensure data designs are aligned with application requirements.
• Develop and maintain data models, data warehouses, data lakes and data marts to support data analysis and reporting.
• Architect and design robust data integration solutions (ETL/ELT) for moving data between various systems and applications.
• Create data pipelines for more efficient and repeatable data science projects.
• Develop and maintain a deep understanding of data platforms, technologies, and tools, and evaluate new technologies and solutions to improve data management processes.
• Develop and maintain data models, data warehouses, data lakes and data marts to support data analysis and reporting.
• Ensure data quality, accuracy, and consistency across all data sources.
• Establish and enforce data governance policies, procedures, and standards to ensure data accuracy, consistency, and compliance.
• Ensure compliance with regulatory and industry standards for data management and security.
• Identify and mitigate technical risks, ensuring the stability and integrity of our digital systems.
• Mentor and coach senior engineers, fostering their technical growth and leadership capabilities.
• Champion Agile principles and practices at an organizational level, promoting cross-functional collaboration and continuous improvement.
• Stay abreast of industry trends, emerging technologies, and competitive landscapes to inform strategic architectural decisions.
• Lead proof-of-concepts and pilot projects for new technologies and architectural approaches.

Required Skills & Experience:

• Bachelors or Masters degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
• 5 years of experience in data architecture, data engineering, or a similar role.
• Proven experience in designing and implementing large-scale, complex data solutions in one or more domains.
• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with programming languages such as Python, Java, or Scala.
• Knowledge of big data technologies such as Hadoop, Spark, snowflake, databricks, and Kafka to process and analyze large volumes of data.
• Skilled in using relational database technologies such as MySQL, PostgreSQL, and Oracle, as well as NoSQL databases such as MongoDB and Cassandra. Strong expertise in cloud-based databases such as AWS 3/ AWS glue, AWS Redshift, Iceberg/parquet file format.
• Experience with data visualization tools such as Tableau, Power BI, or QlikView.
• Understanding of analytics and machine learning concepts and tools.
• Strong data modeling, data warehousing, and data integration skills.
• Knowledge of data governance, data quality, and data security best practices
• Experience with API design and microservices architecture.
• Experience defining and implementing CI/CD pipelines, DevOps practices, and automated testing frameworks.
• Expertise in performance optimization, scalability, and security best practices.
• Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.
• Strong strategic thinking and problem-solving skills, with a track record of delivering innovative solutions.
• Deep understanding of Agile methodologies and experience driving their adoption at an organizational level.

Preferred Skills:

• Deep understanding of data warehousing concepts, ETL/ELT - data transformation & standardization, and data lake architectures.
• Knowledge of data security principles and best practices.
• Familiarity with machine learning concepts and how data architecture supports ML workflows.
• Certifications in cloud data platforms (e.g., AWS Certified Data Analytics - Specialty, Azure Data Engineer Associate) or Snowflake Certifications.
• Proficiency in data visualization tools (e.g., Tableau, Power BI)
• Experience with DevOps practices and CI/CD pipelines for data solutions.