Data Architect – Integration
Job Description
<ul><li>Participates in vendors assessment and selection</li><li>Participates with presales team in the proposed solution design in the bidding phase</li><li>Prepares the Scope of Work (SoW) proposal write-up for bidding in software projects</li><li>Prepares professional services sizing, assumptions, and pre-requisites for bidding in software projects</li><li>Participates in customer demonstrations and presentations to discuss and convince the customer by our software solutions</li><li>Attend requirement gathering workshops and prepares business requirements documents</li><li>Collaborate with stakeholders, including business analysts, data scientists, and IT teams, to understand data requirements and define data solutions</li><li>Evaluate existing data systems and infrastructure, identify areas for improvement, and propose and implement solutions to optimize data management processes</li><li>Define data standards, guidelines, and best practices to ensure data quality, consistency, and security across the organization</li><li>Develop and maintain data models, data dictionaries, and metadata repositories to facilitate data governance and data lineage</li><li>Stay up to date with industry trends and emerging technologies in data management and make recommendations for adopting new tools and techniques</li><li>Lead data integration efforts, including data ingestion, transformation, and integration processes, to support data analytics and reporting requirements</li><li>Provide guidance and mentorship to junior data professionals and facilitate knowledge sharing within the organization</li></ul><p><br></p><strong>Requirements</strong><p><br></p><ul><li>B.Sc. of Engineering or Computer Science or relevant</li><li>Strong Data Management Knowledge: A data architect should have a solid understanding of data management principles, including data modeling, data integration, data quality, data governance, and data lifecycle management. </li><li>Database Systems: Proficiency in working with various database systems, such as relational databases (e.g., Oracle, SQL Server, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra), is essential. Familiarity with data warehousing concepts and technologies (e.g., Snowflake, Amazon Redshift) is also beneficial. </li><li>Data Modeling: Data architects should be skilled in data modeling techniques and tools, such as entity-relationship diagrams (ERDs) and dimensional modeling. Knowledge of industry-standard modeling notations like UML (Unified Modeling Language) and familiarity with tools like ERwin, PowerDesigner, or ER/Studio can be advantageous. </li><li>ETL (Extract, Transform, Load) and Data Integration: Understanding the principles and practices of ETL processes and data integration is crucial for a data architect. Proficiency in ETL tools like Informatica, Talend, or Microsoft SSIS is valuable. </li><li>Data Governance and Compliance: Knowledge of data governance frameworks, policies, and best practices is important. </li><li>Programming and Scripting: Proficiency in programming languages like SQL, Python, or Java is valuable</li><li>Certified Data Management Professional (CDMP) by DAMA International</li><li>Microsoft Certified: Azure Data Engineer Associate</li><li>AWS Certified Big Data – Specialty</li><li>IBM Certified Data Architect – Big Data</li><li>Good command of the English language</li><li>Strong problem-solving and analytical skills</li><li>Excellent communication and collaboration skills</li><li>Ability to work well in a team environment</li><li>Attention to detail and ability to manage multiple tasks simultaneously</li><li>Strong time management and organizational skills</li></ul>
