Engineering Director - D&BA @ Sapiens

As the Data Engineering and Development Director, you will steer organization's technical endeavours in data management, engineering, architecture design and software development of data and analytics products. Your multifaceted role encompasses strategic direction, team leadership, and technical innovation, all converging to deliver impactful data-driven solutions that fuel our business growth. Experience of leading engineering teams with a focus on Data & Analytics products is a crucial qualification we seek in potential candidates.

Your main responsibilities will include:

• Strategy and Planning: Develop and execute a comprehensive data engineering and development strategy aligned with the organization's overall goals.
• Technical Leadership: Provide visionary technical leadership to data engineering and development teams, fostering innovation and excellence. Stay abreast of emerging technologies and industry trends, evaluating their potential impact on our data and analytics capabilities.
• Technical Roadmap: Engage with executive leadership, cross-functional teams, external partners and customers to define technical roadmap for data and analytics products. Ensure successful & timely release of roadmap items.
• Collaboration and Communication: Collaborate with cross-functional teams to seamlessly integrate data products and solutions into business processes. Effectively communicate complex technical concepts to non-technical audiences.
• Architecture and Design: Define and design robust architecture for data pipelines, databases, data warehouses, and other data-related infrastructure. Ensure scalability, efficiency, and alignment with evolving business needs.
• Agile Approach to Data Warehousing & BI: Implement Agile methodologies for data warehousing and business intelligence product development, fostering adaptability and rapid delivery.
• Data Integration and ETL/ELT/ML: Oversee design and implementation of data integration processes, ETL/ELT/ML workflows, and data transformations. Ensure data consistency, quality, and accuracy across the data lifecycle.
• Delivery & Budget Management: Manage scope, requirements, and timelines for data engineering and software development projects. Ensure effective project execution, monitor progress, and mitigate risks. Manage the departmental budget, allocate resources effectively, and optimize spending for ROI.
• Team Management: Lead recruitment, hiring, onboarding, and training of data engineers, developers, and technical specialists. Foster a culture of collaboration, growth, and technical excellence within the team.
• Continuous Improvement: Evaluate existing processes and systems, identifying opportunities for optimization and enhancement ensuring consistency, efficiency, and quality.
• Technology/Product Feature Showcase and Presentations: Conduct / drive webinars and sessions to showcase technical capabilities, product features, and advancements in data & analytics products to internal and external stakeholders.

What to Have for this position.

Must have Skills.

• Masters degree in computer science/MCA, Engineering, Information Technology, or a related field.
• Professional certifications and experience in areas of data engineering, cloud platforms (AWS, Azure, GCP), big data technologies (Hadoop, Spark), and project management (PMP, Agile) is desirable.
• Min 15 years of experience within IT space with a strong experience on data engineering, development, and analytics.
• At least 8 to 10 years of firsthand experience in Data Warehousing, Big Data, Business Analytics, Machine Learning, Data visualization tools and relevant technologies is must.
• Proven experience in leading, managing & mentoring cross-functional teams, including data engineers, developers, analysts, and architects is desirable.
• Previous roles in R&D, solution architecture, technical leadership, agile methodologies, and project management are advantageous.
• Experience in contributing to research and development initiatives, innovation projects, and technical advancements can be a significant asset.
• Experience in the insurance domain or relevant industries is preferred.
• Technical proficiency in data engineering, ETL processes, data modelling and design principles (e.g. Inmon/Kimball/Data Volt), database design is good to have.
• Firsthand experience with data integration tools, data pipelines, and workflow orchestration is good to have.
• Strong programming skills in languages like Python, Java, Scala, or SQL are advantageous.
• Effective communication and collaboration skills are expected.