We are seeking an experienced and dynamic Technology Leader/ Head - Data to oversee and lead a wide range of data initiatives, with a primary focus on the migration of on-premises infrastructure to AWS. This role will also involve strategic leadership in the areas of Big Data, AI/ML, BI Tools, and managing lift-and-shift data projects. The ideal candidate will have a deep understanding of data architectures, cloud technologies, and advanced analytics, with a proven track record in leading complex technical projects and building high-performing teams.
Key Responsibilities:
Lead On-Premises to AWS Migration:
Oversee the end-to-end migration strategy and execution for moving data workloads and applications from on-premises to AWS cloud infrastructure.
Ensure seamless migration of data platforms, systems, and applications while minimizing downtime and optimizing for cost, performance, and security.
Implement scalable data architectures that align with cloud-native design principles.
Big Data & Cloud Infrastructure Management:
Architect and implement Big Data solutions using AWS services like Redshift, S3, EMR, Kinesis, etc.
Design and maintain robust data pipelines, ensuring high availability, data integrity, and performance.
Leverage cloud-based analytics to process large-scale datasets and derive actionable insights.
AI/ML Strategy and Implementation:
Drive the development of AI/ML models and solutions to extract business value from data.
Collaborate with cross-functional teams to identify AI/ML opportunities and drive model deployment at scale using AWS services like SageMaker.
Provide thought leadership on the adoption of emerging AI/ML technologies.
Business Intelligence (BI) Tools Integration:
Lead the integration and implementation of BI tools (e.g., Power BI, Tableau, Looker, etc.) for data visualization and reporting.
Design and deploy data models for efficient reporting and decision-making across the organization.
Ensure that business users have timely access to data insights via user-friendly dashboards and reports.
Data Governance & Security:
Ensure compliance with relevant data protection regulations, such as GDPR, and maintain security best practices for data management in the cloud.
Define and implement data governance policies around data quality, access control, and metadata management.
Maintain a strong focus on data security, privacy, and disaster recovery planning during the migration and beyond.
Leadership and Team Development:
Lead a team of data engineers, data scientists, and analysts, providing technical direction and mentorship.
Foster a collaborative and innovative work environment, encouraging knowledge sharing and best practices.
Manage stakeholder expectations, project timelines, and resources while delivering high-quality results.
Lift-and-Shift Data Projects:
Oversee the execution of lift-and-shift data migration projects, ensuring that legacy systems are efficiently moved to the cloud.
Assess legacy data architectures and recommend modernizations to optimize cloud-based performance.
Collaborate with various teams to ensure minimal business disruption during the migration process.
Minimum Qualifications:
Technical Skills:
Strong experience with AWS cloud technologies, including EC2, S3, Redshift, EMR, Lambda, RDS, Kinesis, SageMaker, etc.
Expertise in Big Data technologies such as Hadoop, Spark, Kafka, and NoSQL databases.
Experience in designing and deploying AI/ML solutions in production environments.
Proficiency with BI tools such as Power BI, Tableau, or Looker.
Deep knowledge of data architecture, ETL processes, and cloud data management practices.
Familiarity with data security best practices in cloud environments.
Leadership Skills:
Proven track record of leading and managing cross-functional teams, particularly in the areas of data, AI/ML, and cloud migration.
Strong communication and interpersonal skills with the ability to influence stakeholders at all levels.
Ability to drive complex projects forward while managing multiple priorities and tight deadlines.
Experience:
15+ years of experience in data engineering, data architecture, or cloud infrastructure roles.
5+ years of hands-on experience in AWS cloud environments and Big Data technologies.
Strong background in managing data migrations, particularly in lift-and-shift scenarios.
Solid understanding of AI/ML lifecycle, from data preparation to model deployment and optimization.
Education:
Bachelors degree in Computer Science, Information Technology, or a related field (Masters degree preferred).
Additional Qualification:
AWS certifications (e.g., AWS Certified Solutions Architect, AWS Certified Big Data Specialty) are a plus.
Experience with Agile methodologies and DevOps practices in data environments.