In the ever-evolving landscape of data management and technology, the role of a Data Architect has become increasingly pivotal. As businesses across the globe continue to recognize the immense value of data in decision-making, strategy, and innovation, the demand for skilled Data Architects has surged. But what exactly are companies looking for in this critical role?

In this comprehensive exploration, we delve into the heart of what makes a Data Architect invaluable to modern organizations. By meticulously analyzing a plethora of job descriptions sourced from LinkedIn and various online platforms, we aim to uncover the real expectations and qualifications that companies are seeking in their quest for data architecture excellence.

From the intricate technical skills to the broader understanding of business processes, we will dissect the key components that constitute the ideal Data Architect in today’s corporate world. Whether you’re a seasoned professional looking to stay ahead in your career, a budding data enthusiast curious about the field, or a hiring manager seeking to refine your recruitment strategy, this post promises to shed light on the multifaceted nature of this vital role.

Join us as we navigate through the maze of requirements, responsibilities, and expectations, piecing together the complete picture of a Data Architect’s professional landscape in the contemporary business environment.

Responsibilities

  • Develop data strategy by translating business needs into data requirements, e.g. data sources, data streams and integrations.
  • Define data architecture framework, standards and principles.
  • Lead teams of data architects, data engineers, data governance managers and other key stakeholders in a fast-paced cross-functional and diverse environment
  • Spearhead the development and execution of data governance framework, with a focus on data quality and master data management technologies.
  • Design, deploy and configure new data analytics solutions directly in cloud according to best practices.
  • Monitor data analytics cloud applications performance for potential bottlenecks and resolving performance issues.
  • Identify and implement cost-saving strategies to reduce ongoing data analytics and engineering cloud expenses.
  • Lead data architects and engineers on data security, data retention and data privacy to ensure solutions provided to the business meet the regulatory and policy standards.
  • Build data pipelines and functions for data visualization and business analytics supporting the business and respective product owners.
  • Make data management recommendations based on data and industry practices.
  • Collaborate with the technical architecture team and digital solutions team to set up the technologies to realize the data strategy.
  • Collaborate with stakeholders to build data management and governance capabilities.
  • Developing and implementing an overall organizational data management that is in line with Org Data Standards and Data Strategy, includes data model designs, database development standards, implementation and management of data storage (e.g. lakes, warehouses) and data analytics systems
  • Identifying data sources requirements, both internal and external to design the end-to-end data architecture, from developing the meta-data to testing and implementing the proposed data management flow and solution
  • Defining and managing the flow of data and dissemination of information within the organization
  • Collaborate with Data Stewards to create and maintain clear meta and data
  • Define roadmap to transform data architecture focusing on scalability, performance and flexibility throughout the entire data life cycle (ingestion, storage and consumption).
  • Maintain data architecture framework, standards and principles including modeling, metadata, security, master and reference data
  • Define reference architecture as a set of patterns that can leveraged by diverse parts of the direction to create and improve data systems.
  • Lead architectural designs solution context diagram and conceptual data model to optimize security, information leverage and reuse, integration, performance, and availability and ensure solutions developed adhere and aligns to the delivered architecture.
  • Consult and influence digital application teams regarding solutions. Collaborate with other staff to design and implement effective technology solutions, while using innovative business and technology processes to identify and implement improvement initiatives, eliminate redundancies, and maximize the reuse of data.
  • Work closely with Solutioning, Infrastructure and project teams to understand their needs and ensure the best data architecture is implemented.
  • Provide training and share best practices across teams regarding data architecture design and solution implementation including review and quality assurance.
  • Develop and apply industry best practice technology, design and methodology approaches to design bank’s data architecture. Research and recommend new emerging technologies, techniques and tools that will add value to the organization
  • Develop new and improve existing data pipeline on Big Data platform (Hadoop, Hive, HBase, Clickhouse, etc or equivalent)
  • Design and implement API database (MongoDB or equivalent) to support Data REST API
  • Design and implement streaming platform (Kafka or equivalent) to near real time data streaming
  • Manage new and enhance existing data application for streaming and batch datasets
  • Manage Apache Airflow data pipeline, Python, Spark, Scala, Java, etc open sources technologies
  • Manage and govern data protection, data security and InfoSec.
  • Drive optimization, testing and tooling to improve data quality
  • Design high level & detailed design of data platform solution and integration and align to the data & analytics architecture principles and roadmap
  • Collaborate with different stakeholders from business, technical, project management and operation to design and implement the solution.
  • Ensure best practices, frameworks and system integration with security control and resiliency
  • Ability to lead troubleshooting for system integration, data pipeline operation and system issue faced by the project and operation team.
  • Understand various data security standards, information security standard and to apply and adhere to the required data controls for user access
  • Architect the data platform migration and hybrid cloud solutioning
  • Manage Service Delivery for the deliverables related to data platform from either in house development team or vendors.
  • Lead Incident Management and provide timely update to the Management and accountable for technical system issues and root cause analysis
  • Ensure and govern the data systems update to the latest stable Software version. Ensure the system updated with the Periodic patch updates (OS, software, Firmware, Switches, Firewall) – Half yearly/yearly.
  • Conduct necessary POC/trial and perform R&D on the right technologies on the data platform/solution
  • Demonstrable project implementation experience in the manufacturing, aerospace, automotive or similar advanced engineering industry
  • Strong experience in data integration, ETL, data lakes, and creation of modern data platforms
  • Experience with SQL and strong programming skills in a modern language (Python/Kotlin/Java/Scala)
  • Be able to review technical designs and provide constructive feedback
  • Looking to build robust, scalable and reliable software and solutions
  • Progressing data standards and best practices for engineering excellence
  • Maintaining our documentation culture
  • Good Experience on SAP Data migration strategy to migrate from ECC/Non-SAP to SAP S4 HANA as using SAP Business Objects Data Services (BODS 4.2)
  • Strong Data Migration background
  • Work experience on various transformations like Map Operation, Table Comparison, Row-Generation, History Preserving, Query and SQL transformation.
  • Should Possess very good SQL experience
  • Experience with admin console, designer and server manager tools BODS Server and client tools installation experience
  • Working experience in loading data through IDOCs, Files, RFC and LSMW.
  • Experience in performance tuning and code optimization
  • Experience in BODS scripting and Batch scripting.
  • Experience in integration with different system like SAP Applications, HANA and RDBMS source systems
  • Receives direction rather than supervision
  • Able to act independently, seeking consultation guidance and advice as appropriate
  • Ability to understand cross functional data
  • Ensure deliverables are prepared in good quality and on time
  • Need to be proactive in highlighting the issues / risks
  • Knowledge in SOLMAN/Charm Process and Power BI or LTMC is an added advantage.

Requirements

  • Degree holder in Information Systems, Information Technology or Computer Science with 8 years or more experience as a data architect or data engineer
  • Bachelor / Master’s Degree in Analytics, Applied Mathematics, Computer Science, Information Technology, Engineering or equivalent
  • Strong experience in data technologies (Data Lakehouse, Data Warehouse, Databricks)
  • Experience in designing systems to efficiently handle real-time and batch use-cases
  • Working knowledge of data mining principles: mapping, collecting data from multiple data systems on premises and cloud-based data sources
  • In-depth understanding of and experience in designing structured and unstructured, SQL and NoSQL data repositories
  • Experience working with, creating and maintaining databases and repositories using state-of-the-art data backup, rollback and version control solutions.
  • Proficient with analytics engineering methods and technologies / tools using Python. Azure Cloud proficiency will be an advantage.
  • Experience in working in a diverse organisation and across business processes.
  • Excellent written and oral communication skills
  • Bachelor’s Degree in Computer Science or related discipline.
  • 10+ years of experience designing and building high performance resilient data architectures
  • Strong experience with traditional data technologies (ODS, Data Lake, Data Warehouse).
  • Experience in designing data patterns to support micro-service based application architecture
  • Track record of successfully building container-based big data architectures on top of Kubernetes.
  • Experience in designing systems to efficiently handle real-time and batch use-cases.
  • Degree in Engineering or IT
  • More than 5 years relevant of experience.
  • Technical skills required:
    • System administration
    • System integration
    • Data architect
    • Big data and data warehousing operations.
    • Hadoop and Spark (or equivalent)
    • Python, Linux/Unix, Ansible automation, Shell Scripting
    • Kubernetes, Docker, serverless functions, APIs and Kafka bus
    • Network and Security design
  • Communication and presentation skills
  • People management skills
  • Good technical writing skills
  • Excellent communication and presentation skills in English
  • At least 5 years of experience in data architecture, data modelling, and data management
  • Feel strongly about data and want to empower the organisation with it
  • Seek technical excellence, self-driven and motivated
  • Bachelors or Masters in Computer Science, Information Systems or other relevant field

 

 

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