Associate Director - Data Architect

The Enterprise Data Architect will enhancethe company's strategic use of data by designing, developing, and implementingdata models for enterprise applications and systems at conceptual, logical,business area, and application layers. This role advocates data modelingmethodologies and best practices. We seek a skilled Data Architect with deepknowledge of data architecture principles, extensive data modeling experience,and the ability to create scalable data solutions. Responsibilities includedeveloping and maintaining enterprise data architecture, ensuring dataintegrity, interoperability, security, and availability, with a focus onongoing digital transformation projects.

Key Responsibilities

1. Strategy Planning

o Develop and deliver long-term strategic goalsfor data architecture vision and standards in conjunction with data users,department managers, clients, and other key stakeholders.

o Create short-term tactical solutions toachieve long-term objectives and an overall data management roadmap.

o Establish processes for governing theidentification, collection, and use of corporate metadata; take steps to assuremetadata accuracy and validity.

o Establish methods and procedures for trackingdata quality, completeness, redundancy, and improvement.

o Conduct data capacity planning, life cycle,duration, usage requirements, feasibility studies, and other tasks.

o Create strategies and plans for data security,backup, disaster recovery, business continuity, and archiving.

o Ensure that data strategies and architecturesare aligned with regulatory compliance.

o Develop a comprehensive data strategy incollaboration with different stakeholders that aligns with the transformationalprojects goals.

o Ensure effective data management throughoutthe project lifecycle.

2. Acquisition Deployment

o Ensure the success of enterprise-levelapplication rollouts (e.g. ERP, CRM, HCM, FPA, etc.)

Liaise with vendorsand service providers to select the products or services that best meet company goals

3. Operational Management

• Assess and determine governance, stewardship, and frameworks for managing data across the organization.
• Develop and promote data management methodologies and standards.
• Document information products from business processes and create data entities
• Create entity relationship diagrams to show the digital thread across the value streams and enterprise
• Create data normalization across all systems and data base to ensure there is common definition of data entities across the enterprise
• Document enterprise reporting needs develop the data strategy to enable single source of truth for all reporting data
• Address the regulatory compliance requirements of each country and ensure our data is secure and compliant
• Select and implement the appropriate tools, software, applications, and systems to support data technology goals.
• Oversee the mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality.
• Collaborate with project managers and business unit leaders for all projects involving enterprise data.
• Address data-related problems regarding systems integration, compatibility, and multiple-platform integration.
• Act as a leader and advocate of data management, including coaching, training, and career development to staff.
• Develop and implement key components as needed to create testing criteria to guarantee the fidelity and performance of data architecture.
• Document the data architecture and environment to maintain a current and accurate view of the larger data picture.
• Identify and develop opportunities for data reuse, migration, or retirement.

4. Data Architecture Design:

• Develop and maintain the enterprise data architecture, including data models, databases, data warehouses, and data lakes.
• Design and implement scalable, high-performance data solutions that meet business requirements.

5. Data Governance:

• Establish and enforce data governance policies and procedures as agreed with stakeholders.
• Maintain data integrity, quality, and security within Finance, HR and other such enterprise systems.

6. Data Migration:

• Oversee the data migration process from legacy systems to the new systems being put in place.
• Define & Manage data mappings, cleansing, transformation, and validation to ensure accuracy and completeness.

7. Master Data Management:

• Devise processes to manage master data (e.g., customer, vendor, product information) to ensure consistency and accuracy across enterprise systems and business processes.
• Provide data management (create, update and delimit) methods to ensure master data is governed

8. Stakeholder Collaboration:

• Collaborate with various stakeholders, including business users, other system vendors, and stakeholders to understand data requirements.
• Ensure the enterprise system meets the organization's data needs.

9. Training and Support:

• Provide training and support to end-users on data entry, retrieval, and reporting within the candidate enterprise systems.
• Promote user adoption and proper use of data.

10. Data Quality Assurance:

• Implement data quality assurance measures to identify and correct data issues.
• Ensure the Oracle Fusion and other enterprise systems contain reliable and up-to-date information.

11. Reporting and Analytics:

• Facilitate the development of reporting and analytics capabilities within the Oracle Fusion and other systems
• Enable data-driven decision-making through robust data analysis.

1.Continuous Improvement:

• Continuously monitor and improve data processes and the Oracle Fusion and other system's data capabilities.
• Leverage new technologies for enhanced data management to support evolving business needs.

Technology and Tools:

• Oracle Fusion Cloud
• Data modeling tools (e.g., ER/Studio, ERwin)
• ETL tools (e.g., Informatica, Talend, Azure Data Factory)
• Data Pipelines: Understanding of data pipeline tools like Apache Airflow and AWS Glue.
• Database management systems: Oracle Database, MySQL, SQL Server, PostgreSQL, MongoDB, Cassandra, Couchbase, Redis, Hadoop, Apache Spark, Amazon RDS, Google BigQuery, Microsoft Azure SQL Database, Neo4j, OrientDB, Memcached)
• Data governance tools (e.g., Collibra, Informatica Axon, Oracle EDM, Oracle MDM)
• Reporting and analytics tools (e.g., Oracle Analytics Cloud, Power BI, Tableau, Oracle BIP)
• Hyperscalers / Cloud platforms (e.g., AWS, Azure)
• Big Data Technologies such as Hadoop, HDFS, MapReduce, and Spark
• Cloud Platforms such as Amazon Web Services, including RDS, Redshift, and S3, Microsoft Azure services like Azure SQL Database and Cosmos DB and experience in Google Cloud Platform services such as BigQuery and Cloud Storage.
• Programming Languages: (e.g. using Java, J2EE, EJB, .NET, WebSphere, etc.)
• SQL: Strong SQL skills for querying and managing databases
• Python: Proficiency in Python for data manipulation and analysis.
• Java: Knowledge of Java for building data-driven applications.
• Data Security and Protocols: Understanding of data security protocols and compliance standards.

Education:

• Bachelor’s degree in computer science, Information Technology, or a related field. Master’s degree preferred.

Experience:

• 10+ years overall and at least 7 years of experience in data architecture, data modeling, and database design.
• Proven experience with data warehousing, data lakes, and big data technologies.
• Expertise in SQL and experience with NoSQL databases.
• Experience with cloud platforms (e.g., AWS, Azure) and related data services.
• Experience with Oracle Fusion or similar ERP systems is highly desirable.

Skills:

• Strong understanding of data governance and data security best practices.
• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills.
• Ability to work effectively in a collaborative team environment.
• Leadership experience with a track record of mentoring and developing team members.
• Excellent in documentation and presentations.
• Good knowledge of applicable data privacy practices and laws.

Certifications:

• Relevant certifications (e.g., Certified Data Management Professional, AWS Certified Big Data – Specialty) are a plus.
• Behavioral
• A self-starter, an excellent planner and executor and above all, a good team player
• Excellent communication skills and inter-personal skills are a must
• Must possess organizational skills, including multi-task capability, priority setting and meeting deadlines
• Ability to build collaborative relationships and effectively leverage networks to mobilize resources
• Initiative to learn business domain is highly desirable
• Likes dynamic and constantly evolving environment and requirements