Data Architect

About The Role

The Data Architect plays a critical role in designing, implementing, and managing the enterprise data architecture for ELGi, ensuring that data platforms, systems, and solutions are scalable, efficient, and aligned with business needs.

Role & responsibilities

Data Architecture Design and Strategy

• Define and implement the enterprise data architecture strategy, ensuring alignment with business and IT objectives.
• Design scalable, secure, and cost-effective data platforms, including data lakes, data warehouses, and real-time streaming solutions.
• Develop data models and integration frameworks to support analytics, reporting, and business intelligence (BI) initiatives.
• Drive the adoption of cloud-based data platforms (e.g., AWS, Azure, GCP) and modern data technologies to enable enterprise-wide analytics.

Data Governance and Standards

• Establish and enforce data architecture standards, frameworks, and best practices.
• Collaborate with data governance teams to ensure high data quality, consistency, security, and compliance (e.g., DPDP, GDPR, CCPA).
• Oversee metadata management, lineage tracking, and the development of data dictionaries.

Collaboration and Solution Delivery

• Partner with business stakeholders, data scientists, and IT teams to understand requirements and deliver fit-for-purpose data solutions.
• Support the design and implementation of data pipelines for ingesting, processing, and transforming structured and unstructured data.
• Act as a subject matter expert for data architecture across key IT and business initiatives, ensuring seamless integration and performance.

Innovation and Emerging Technologies

• Evaluate and recommend emerging data technologies, tools, and frameworks (e.g., AI/ML, IoT data integration, edge computing) to drive innovation.
• Lead proof-of-concept (PoC) initiatives to explore advanced data solutions and improve existing architecture.
• Incorporate sustainability (Green IT) principles into data architecture design.

Team Leadership and Mentoring

• Provide technical leadership and mentorship to a team of data engineers and analysts.
• Work closely with cross-functional teams to enable data-driven decision-making through modern, sustainable data strategies and technologies.
• Foster a culture of continuous improvement, collaboration, and technical excellence.

Preferred candidate profile

Skills

• Proficiency in designing and implementing enterprise data architectures for large, complex organizations.
• Strong hands-on experience with cloud platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery), big data tools (e.g., Spark, Hadoop), and relational and NoSQL databases.
• Expertise in data modeling (conceptual, logical, and physical), ETL/ELT pipelines, and data integration tools.
• Familiarity with modern data platforms, such as data lakes, lakehouses, and data mesh architectures.
• Experience with real-time data streaming tools (e.g., Apache Kafka, AWS Kinesis) and API integrations.
• Leadership and Problem-Solving skills with excellent collaboration skills to work cross-functionally with IT, business units, and senior stakeholders.
• Ability to translate technical concepts into business-friendly language for non-technical stakeholders.

Experience

• 8-10 years of experience in data architecture, data engineering, or related roles.
• Demonstrated experience designing and implementing enterprise-scale data platforms in a manufacturing or industrial environment.
• Proven track record of delivering successful data solutions that enable analytics and decision-making

Education

• Bachelors degree in Computer Science, Information Technology, Engineering or a related field (Masters Degree preferred)

Certifications

• Cloud Data Architect Certification (e.g., AWS Certified Data Analytics Specialty, Azure Data Engineer Associate, GCP Professional Data Engineer).
• DAMA Certified Data Management Professional (CDMP) (preferred).
• Certiifications in big data tools or data modeling frameworks (e.g., Snowflake, Databricks) are a plus.