Description : Hiring Data Architect for Bangalore Location.

Experience - 11-17 Yrs

Job Location - Bangalore

Job Description :

AI Technology Strategy & Implementation:

- Oversee the design, development, and maintenance of scalable and secure data architectures that support AI and machine learning initiatives.

- Ensure the integration of AI models and algorithms with data infrastructure to enable seamless deployment and operationalization.

- Evaluate and implement cutting-edge data engineering technologies and tools to enhance data processing capabilities and support AI initiatives.

Project & Program Management :

- Lead the planning, execution, and delivery of large-scale, complex data engineering projects, ensuring they are completed on time, within scope, and within budget.

- Implement robust project management methodologies, including Agile and DevOps practices, to enhance project efficiency and effectiveness.

- Coordinate with global teams to ensure alignment and consistency in data engineering practices and solutions across all regions.

Stakeholder Engagement & Collaboration :

- Collaborate with key stakeholders, including data scientists, AI developers, business leaders, and IT departments, to understand data requirements and deliver solutions that meet business needs.

- Facilitate effective communication and collaboration between technical and non-technical stakeholders to ensure alignment and transparency.

- Present data engineering strategies, project updates, and performance metrics to executive leadership and other stakeholders.

Data Governance, Security & Compliance :

- Establish and enforce data governance policies, ensuring data quality, integrity, and security across all AI initiatives.

- Ensure compliance with relevant data privacy laws, regulations, and industry standards (e.g., GDPR, CCPA).

- Implement robust data security measures to protect sensitive information and mitigate risks.

Performance Monitoring & Optimization :

- Develop and monitor key performance indicators (KPIs) to assess the effectiveness and efficiency of data engineering solutions.

- Analyze performance data to identify areas for improvement and implement optimization strategies.

- Lead post-implementation reviews to gather feedback, optimize data engineering processes, and ensure sustained value delivery.

Continuous Innovation & Improvement :

- Stay abreast of the latest trends, technologies, and best practices in data engineering and AI to drive continuous improvement and innovation.

- Promote a culture of continuous learning and adaptability within the data engineering team.

- Identify opportunities for automation and process enhancement to improve data engineering workflows and outcomes.

Qualifications :

Education :

- Bachelors degree in Computer Science, Data Science, Information Technology, Engineering, or a related field. A Masters degree or MBA is highly preferred.

Experience :

- Minimum of 11+ years of experience in data engineering, data architecture, or a related role within a professional services or technology-driven environment.

- Proven track record of leading large-scale, complex data engineering initiatives that support AI/ML applications.

- Extensive experience in designing and implementing scalable data architectures and managing data engineering teams in a global context.

- Demonstrated expertise in integrating AI models with data infrastructure to enable operationalization and deployment.

Certifications :

- Relevant certifications in data engineering, cloud platforms, or big data technologies (e.g., Google Professional Data Engineer, AWS Certified Big Data Specialty) are advantageous.

- Certifications in project management (e.g., PMP, PRINCE2) are a plus.

Skills and Competencies :

Strategic Leadership :

- Exceptional leadership and strategic thinking skills with the ability to develop and execute long-term data engineering strategies.

- Ability to influence and drive change across multiple teams and regions.

Technical Expertise :

- Deep knowledge of data engineering principles, including data pipeline development, data architecture, and data modeling.

- Proficiency in programming languages such as Python, Java, or Scala, and strong SQL skills.

- Expertise in big data technologies and frameworks (e.g., Hadoop, Spark, Kafka) and cloud platforms (e.g., AWS, Azure, Google Cloud).

- Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

AI & Machine Learning Integration :

- Strong understanding of AI/ML concepts, algorithms, and their integration with data engineering solutions.

- Experience with AI frameworks and tools such as TensorFlow, PyTorch, or scikit-learn.

Project & Program Management :

- Advanced project management skills with experience managing multiple high-impact projects simultaneously

- Proficiency in Agile methodologies and project management tools (e.g., Jira, Trello).

Data Governance & Security :

- In-depth knowledge of data governance principles, data privacy regulations, and best practices in data security.

- Experience implementing data governance frameworks and ensuring compliance with relevant regulations.

Analytical & Problem-Solving Skills :

- Strong analytical abilities to assess complex data engineering challenges and develop innovative solutions.

- Excellent troubleshooting skills to identify and resolve technical issues efficiently.

Communication & Collaboration :

- Superior verbal and written communication skills, with the ability to convey complex technical concepts to diverse audiences.

- Strong interpersonal skills to build and maintain relationships with stakeholders at all levels.

Adaptability & Innovation :

- Ability to thrive in a fast-paced, dynamic environment and adapt to evolving business needs and technologies.

- Passion for continuous learning and staying updated with the latest advancements in data engineering and AI.