Data Engineering Manager

The position will lead the data platform strategy and execution for our organization. This role involves leading the development and implementation of Indus Data Platform, including data ingestion, integration, governance, analytics, and visualisation to drive business insights and innovation. The ideal candidate will have a strong technical and data an optional AI/ML background, great execution capabilities, and a mindset to build and manage a high-performing team.

The core responsibilities for the job include the following:

Leadership:
• Develop and execute the data strategy in alignment with the company's business goals.
• Lead and mentor a team of data engineers, data scientists, and analysts.
• Create a culture of data-driven decision-making, and collaborate with senior leadership to influence company strategy and direction through data-driven insights.

Data Engineering:
• Design and implement scalable data pipelines to collect, process, and store data from various sources, especially high-throughput telemetry data from field sensors (IoT) and other multi-modal (text, images, video) data sources.
• Ensure data quality, integrity, and security across all data systems.
• Oversee the development of data architecture and infrastructure to support analytics and data science initiatives.

Data Governance and Management:
• Establish Data quality standards and procedures.
• Implement data governance policies and procedures.
• Develop and maintain data models and reporting systems that are open to business users.

Analytics and Data Science:
• Lead the development of advanced analytics and machine learning models to solve complex business problems.
• Implement MLOps - AI/ML/Gen-AI on top of the data platform.
• Drive the adoption of data-driven decision-making across the organization.

Requirements:
• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• Proven experience in data engineering, analytics in product companies.
• Strong background in designing and implementing data pipelines and architectures, especially on AWS stack (S3 iceberg, Redshift, sagemaker, Glue, MSK, RDS, QuickSight).
• Experience with large-scale data technologies, cloud platforms, AI/ML/Gen-AI platforms, and data visualization tools.
• Proficiency in programming languages such as Python, SQL, R, Spark, or more, and experience with machine learning frameworks and data architecture.

Skills:
• Hands-on technology leader.
• Excellent leadership and team management skills.
• Strong analytical and problem-solving abilities.
• Ability to communicate complex technical concepts to non-technical stakeholders.