Software Engineering Lead - Data Engg, AWS, Redshift, Kinesis, Tableau

Primary Responsibilities:

• Design and implement data models to analyse business, system, and security events for real-time insights and threat detection
• Conduct exploratory data analysis (EDA) to understand patterns and relationships across large data sets, and develop hypotheses for new model development
• Develop dashboards and reports to present actionable insights to business and security teams
• Build and automate near real-time analytics workflows on AWS, leveraging services like Kinesis, Glue, Redshift, and QuickSight
• Collaborate with AI/ML engineers to develop and validate data features for model inputs
• Interpret and communicate complex data trends to stakeholders and provide recommendations for data-driven decision-making
• Ensure data quality and governance standards, collaborating with data engineering teams to build quality data pipelines
• Develop data science algorithms & generate actionable insights as per platform needs and work closely with cross capability teams throughout solution development lifecycle from design to implementation & monitoring
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• B. Tech or BE or Masters degree (MCA) or equivalent experience
• 6+ years of experience in data engineering roles in Data Warehouse
• 2+ years of experience as a Data Scientist with a focus on building models for analytics and insights in AWS environments
• Experience with AWS data and analytics services (e.g., Kinesis, Glue, Redshift, Athena, TimeStream)
• Hands-on experience with statistical analysis, anomaly detection and predictive modelling
• Proficiency with SQL, Python, and data visualization tools like QuickSight, Tableau, or Power BI
• Proficiency in data wrangling, cleansing, and feature engineering

Preferred Qualifications:

• Experience in security data analytics, focusing on threat detection and prevention
• Knowledge of AWS security tools and understanding of cloud data security principles
• Familiarity with deploying data workflows using CI/CD pipelines in AWS environments
• Background in working with real-time data streaming architectures and handling high-volume event-based data