Job Summary:

• We are seeking a highly motivated and skilled Senior Data Engineer with a strong focus on Cloud platforms(GCP/Azure) to join our growing team.
• This role will be critical in driving our data-driven initiatives by developing and maintaining robust data pipelines and preparing high-quality data for machine learning models, with a focus on the unique challenges and data needs of the insurance industry.
• You will have the opportunity to work on cutting-edge projects, leveraging the power of GCP, and contribute to the development of innovative data solutions that improve our business processes and customer experience.

Responsibilities:

• Lead Data Preparation Efforts: Oversee all aspects of data preparation for AI Proof of Concepts (POCs), from data collection and integration to cleaning, transformation, and feature engineering.
• Develop Data Pipelines: Design and implement efficient data pipelines using Google Cloud Dataflow, Cloud Functions, and other GCP services to automate data processing tasks and ensure data quality and consistency.
• Data Structuring & Transformation: Transform raw data into structured formats suitable for analysis, including data warehousing, data lakes, normalization, aggregation, and feature engineering.
• Data Segmentation: Effectively segment data into meaningful subsets based on various criteria (e.g., customer demographics, behavior, risk profiles) to improve model accuracy and insights for insurance applications.
• Data Mining: Extract valuable patterns and insights from large insurance datasets using techniques like association rule mining, clustering, and anomaly detection.
• Collaborate with Data Scientists & Engineers: Work closely with data scientists and engineers to understand their data requirements and translate them into actionable data preparation strategies.
• Ensure Data Security & Compliance: Implement appropriate data anonymization and privacy measures, including techniques like differential privacy, k-anonymity, and l-diversity, to protect sensitive customer data and comply with relevant regulations within Qatar's legal frameworks.
• Process Automation: Leverage data analysis and automation techniques to streamline and optimize business processes.
• Document Data Processes: Maintain clear and comprehensive documentation of all data preparation steps and processes to ensure reproducibility and transparency.
• Stay Updated on Data Technologies: Continuously learn and adapt to new data technologies, tools, and techniques within the Google Cloud ecosystem, with specific attention to applications relevant to the insurance sector.

Required Skills:

• Advanced Python: Strong proficiency in Python with expertise in data manipulation libraries (Pandas, NumPy), data processing frameworks (e.g., Apache Beam), and machine learning libraries (scikit-learn, TensorFlow).
• Google Cloud Platform (GCP): In-depth knowledge of GCP services such as Compute Engine, Cloud Storage, BigQuery, Dataflow, Pub/Sub, and Cloud Functions.
• Data Wrangling & Cleansing: Expertise in cleaning and preparing raw data for analysis, including handling missing values, identifying and correcting inconsistencies, and resolving data quality issues.
• Data Anonymization & Privacy: Deep understanding of advanced data privacy techniques (e.g., differential privacy, k-anonymity, l-diversity, t-closeness) and their implementation.
• AI/ML Model Development: Experience in preparing data for specific machine learning algorithms, including data cleaning, feature selection, and handling imbalanced datasets. Additionally, familiarity with training and evaluating machine learning models, including model selection, hyperparameter tuning, and performance assessment.
• Model Deployment & Monitoring: Understanding of the model deployment process and the importance of ongoing model monitoring and maintenance to ensure accuracy and reliability.

Preferred Qualifications:

• Master's degree in Computer Science, Data Science, Statistics, or a related field.
• Experience with data visualization tools (e.g., Qlik Sense, Tableau, Power BI).
• Familiarity with containerization technologies (e.g., Docker, Kubernetes).
• Experience with AI/ML technologies and their applications within the insurance industry (e.g., fraud detection, customer segmentation, risk assessment).
• Knowledge of insurance industry KPIs and their relevance to business outcomes.
• Experience with Vertex AI Gemini API for natural language processing tasks and integrating with data pipelines.

Additional Considerations:

• Experience with data privacy and compliance regulations specific to Qatar is preferred.
• Arabic language proficiency is a plus.
• Certifications in relevant Google Cloud technologies (e.g., Google Cloud Professional Data Engineer).