Senior Technical Architect - Data Engineering & Modeling

Title : Senior Technical Architect (Data Architect) Remote Are you a Data Architecture expert with hands-on experience in AWS, Data Modeling, and Data Engineering ? Do you have a passion for building scalable data solutions in the Life Insurance domain? If yes, we have an exciting opportunity for you Role : Senior Technical Architect (Data Architect) Location : Remote Experience : 10-12 years What Youll Do : - Architect and implement scalable data solutions using AWS cloud services. - Work extensively with DynamoDB, S3, AWS Glue, Athena, OpenSearch to drive innovation. - Design and optimize ETL workflows using AWS Glue, DMS, and Python. - Manage real-time data streaming with AWS Kinesis and lead data migration initiatives. - Define data models, optimize performance, and ensure scalability of data pipelines. - Lead and mentor offshore teams, ensuring best practices and high-quality deliverables. - Collaborate with stakeholders to align data strategies with business objectives. What Were Looking For : - 10-12 years of experience in Data Architecture & Engineering. - Life Insurance domain expertise is mandatory. - Strong skills in SQL, Python, PySpark for data transformation. - Deep expertise in AWS Data Services DynamoDB, S3, Glue, Athena, OpenSearch. - Experience with Data Migration & Streaming (AWS DMS, Kinesis, Attunity). - Strong stakeholder management and leadership skills to drive projects effectively. Detailed Technical Job Description : As a Senior Technical Architect (Data Architect), you will be responsible for the design, implementation, and management of enterprise-level data architecture solutions on the AWS cloud platform. You will leverage your deep expertise in data modeling, data warehousing, ETL processes, and big data technologies to deliver scalable, high-performance, and cost-effective solutions that meet the complex data needs of our Life Insurance business. You will provide technical leadership, mentor a team of data engineers, and collaborate with stakeholders to drive data-driven : Data Architecture Design : - Develop and maintain the overall data architecture strategy, ensuring alignment with business goals and industry best practices. - Design and implement scalable and robust data solutions on AWS, utilizing services such as DynamoDB, S3, Glue, Athena, OpenSearch, and others. - Define data modeling standards and guidelines for both relational and NoSQL databases. - Create and maintain conceptual, logical, and physical data models. - Design data integration and ETL processes to ensure data quality, consistency, and accuracy. AWS Data Services : Demonstrate deep expertise in a wide range of AWS data services, including : - Database : DynamoDB, RDS (PostgreSQL, MySQL), Aurora - Storage : S3, Glacier - ETL : AWS Glue, Data Pipeline - Data Warehousing : Amazon Redshift - Big Data : EMR, Hadoop, Spark - Streaming : Kinesis Data Streams/Firehose - Search and Analytics : OpenSearch, Athena - Architect and optimize data storage, retrieval, and processing solutions on AWS. - Implement best practices for data security, access control, and compliance on AWS. ETL Development : - Design, develop, and optimize ETL workflows using AWS Glue, AWS DMS, Python, and PySpark. - Implement data quality checks and validation processes. - Automate data ingestion, transformation, and loading processes. - Develop and maintain data pipelines for both batch and real-time data. Data Migration and Streaming : - Lead data migration initiatives from on-premises systems to AWS, utilizing services like AWS DMS and Attunity. - Design and implement real-time data streaming solutions using AWS Kinesis. - Ensure minimal downtime and data loss during migration and streaming processes. Performance Optimization : - Identify and resolve data-related performance bottlenecks. - Optimize database queries, ETL processes, and data pipelines for maximum efficiency. - Implement caching strategies and other techniques to improve data access performance. Leadership and Mentoring: - Lead and mentor offshore teams of data engineers, providing technical guidance and support. - Conduct code reviews and ensure adherence to coding standards and best practices. - Foster a collaborative and knowledge-sharing environment. - Manage project timelines, resources, and deliverables. Stakeholder Collaboration : - Collaborate with business stakeholders, product managers, and other teams to understand data requirements and deliver solutions that meet their needs. - Communicate complex technical concepts clearly and effectively to both technical and non-technical audiences. - Participate in project planning, estimation, and risk management activities. - Align data strategies with business objectives and provide recommendations for data-driven initiatives. Qualifications : Education : Bachelor's or Master's degree in Computer Science, Information Systems, or a related field. Experience : 10-12 years of experience in Data Architecture, Data Engineering, and related roles. Domain Expertise : Mandatory experience in the Life Insurance domain, with a strong understanding of industry data models, business processes, and regulatory requirements. AWS Expertise : - Deep understanding of AWS data services and best practices. - Experience in designing and implementing data solutions on AWS. - AWS certifications (e.g., AWS Certified Data Analytics - Specialty) are highly preferred. Programming Skills : - Strong proficiency in SQL for data querying and manipulation. - Proficiency in Python for data processing, ETL, and automation. - Experience with PySpark for big data processing. Data Modeling : - Extensive experience in data modeling techniques (e.g., dimensional modeling, ER modeling). - Ability to create conceptual, logical, and physical data models. ETL and Data Integration : - Solid understanding of ETL principles and best practices. - Experience with ETL tools and frameworks (e.g., AWS Glue, Informatica, DataStage). Data Migration and Streaming : - Experience with data migration tools and techniques (e.g., AWS DMS, Attunity). - Knowledge of real-time data streaming technologies (e.g., AWS Kinesis, Kafka). Leadership Skills : - Proven ability to lead and mentor technical teams. - Strong project management and organizational skills. - Excellent communication, collaboration, and stakeholder management skills. Problem-solving : - Strong analytical and problem-solving skills (ref:hirist.tech)

Location: in, IN

Posted Date: 4/19/2025