Chief Data Engineer

6 days ago

Delhi, Delhi, India beBeeData Full time ₹ 20,00,000 - ₹ 25,00,000
Key Roles and Responsibilities\We are seeking an experienced Enterprise Data Architect with a strong background in banking to lead the design and implementation of our data-driven initiatives. The ideal candidate will bridge the gap between business needs and technical solutions, creating robust and scalable data architectures that support advanced analytics and machine learning.\The successful candidate must have a proven track record of developing end-to-end data science solutions within a financial institution, ensuring projects are not only technically sound but also aligned with banking-specific regulations and business objectives.\Key Responsibilities:\- Lead the design and architecture of enterprise-level data platforms, pipelines, and machine learning models.\- Translate complex business requirements from banking operations (e.g., fraud detection, credit risk, customer segmentation) into technical data science solutions.\- Develop, deploy, and manage machine learning and AI models in a production environment, ensuring scalability, performance, and reliability.\- Collaborate with data engineers, IT teams, and business stakeholders to ensure data is efficiently collected, stored, and managed.\- Establish data governance, quality, and security standards in compliance with banking regulations (e.g., Basel III, IFRS 9).\- Mentor and guide junior data scientists on best practices in data modeling, algorithm development, and solution architecture.\Required Skills & Qualifications:\- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.\- A minimum of 7 years of proven experience in the banking or financial services sector is mandatory.\- Extensive experience with the full data science lifecycle, from data collection and cleaning to model deployment and monitoring.\- Deep expertise in data architecture, data modeling, and database technologies (SQL, NoSQL).\- Strong proficiency in programming languages like Python and R, with experience in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.\- Excellent communication and leadership skills, with the ability to explain complex technical concepts to non-technical stakeholders.\- Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (AWS, Azure, or GCP).\- Knowledge of banking products, processes, and relevant regulatory requirements.\- Must hold professional certifications such as TOGAF and other related enterprise or solution architecture credentials.

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