SQL Data Engineer

AI-Aware Data Engineer (Oracle, PostgreSQL & Azure)

About the Role
As an AI-Aware Data Engineer, you will make an impact by designing, developing, and optimizing enterprise data solutions that support analytics, reporting, and AI-ready data initiatives. You will be a valued member of the Data Engineering team and work collaboratively with architects, developers, business stakeholders, testers, and operations teams to build scalable, secure, and high-performing data platforms. In this role, you will leverage your expertise in Oracle, PostgreSQL, Azure Data Factory, SSIS, and C# to deliver modern data integration solutions while supporting Life & Annuities insurance business processes and enabling AI-driven insights. In This Role, You Will
- Design and implement efficient data models and integration patterns across Oracle and PostgreSQL environments to support enterprise analytics and reporting.
- Develop and optimize C#-based data services and APIs that interact with relational databases and enterprise data platforms.
- Build, maintain, and optimize scalable data pipelines using Azure Data Factory for ingestion, transformation, and loading of structured and semi-structured data.
- Configure, enhance, and support Microsoft SSIS packages for complex data integration and transformation processes.
- Develop advanced PL/SQL procedures, functions, and packages that support business logic, data validation, and high-volume transactional processing.
- Monitor, troubleshoot, and optimize end-to-end data workflows across Oracle, PostgreSQL, Azure Data Factory, and SSIS environments.
- Collaborate with architecture and application teams to develop secure, scalable, and compliant data solutions aligned with enterprise standards.
- Create and maintain technical documentation, data flow diagrams, process documentation, and operational procedures.
- Prepare high-quality, AI-ready datasets, metadata assets, and curated data structures to support analytics, machine learning, and predictive modeling initiatives.
- Implement data quality controls, validation checks, reconciliation processes, and governance standards that support regulatory and business requirements.
- Translate Life & Annuities insurance concepts, including policies, premiums, claims, and reserves, into scalable data models and reporting solutions.
- Support deployment planning, release validation, production monitoring, and operational support activities within a day-shift environment.
- Communicate effectively with technical and business stakeholders through design discussions, project updates, and issue-resolution activities. Work Model We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring 3 days per week in a client or Cognizant office. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs. The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured, we will always be clear about role expectations. What You Need to Have to Be Considered
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field.
- 8-12 years of experience designing, developing, and supporting enterprise data solutions.
- Strong expertise in Oracle database development, schema design, performance tuning, partitioning, and PL/SQL programming.
- Advanced experience with Azure Data Factory, including pipeline development, orchestration, scheduling, and parameterization.
- Strong experience developing and maintaining Microsoft SSIS packages and enterprise ETL workflows.
- Hands‑on experience with PostgreSQL administration, performance optimization, and query tuning.
- Strong C# development experience building data‑centric services, APIs, and integration solutions.
- Experience designing and implementing scalable data integration and transformation architectures.
- Strong understanding of data governance, data quality, security, and compliance practices.
- Experience working with enterprise cloud and hybrid data environments.
- Strong analytical, problem‑solving, and stakeholder management skills.
- Excellent written and verbal communication skills in English. These Will Help You Stand Out
- Experience supporting Life & Annuities insurance platforms and business processes.
- Knowledge of policy administration, premiums, claims, reserves, underwriting, and insurance reporting.
- Experience preparing AI‑ready datasets and supporting machine learning, predictive analytics, or AI initiatives.
- Familiarity with modern data architecture patterns, including Data Lakes, Data Warehouses, and Lakehouse platforms.
- Experience implementing data observability, monitoring, and autom