Job Description :

The Data Engineering role requires designing, implementing, configuring, and supporting enterprise dbt environments integrated with Amazon Redshift. The role involves managing the dbt platform, configuring users and roles, establishing integrations with existing data and development environments, and developing dbt-based data transformation solutions. The individual will also support secure access to data through natural language and conversational analytics capabilities, ensuring that user access permissions are consistently enforced across the analytics interface, dbt, and underlying Redshift datasets.

Role Description :

We are looking for a Senior Data Engineer to design, develop, and optimize scalable, reliable, and secure data platforms and pipelines. The role requires strong expertise in modern data engineering, cloud data platforms, data architecture, data modeling, and database technologies, with the ability to translate business requirements into high-quality, production-ready data solutions.

Primary Skills : Amazon Redshift

Secondary Skills : Azure DevOps

Role Responsibilities :

- Design, develop, and maintain end-to-end data pipelines, data platforms, and integration solutions across batch and streaming workloads.

- Translate business, functional, and technical requirements into maintainable, production-ready data solutions.

- Build data flows across structured, semi-structured, and unstructured sources using appropriate ingestion and integration patterns.

- Develop data transformation and processing workflows to support large data volumes and evolving business requirements.

- Implement data quality, validation, reconciliation, testing, and observability practices across data pipelines.

- Optimize data pipelines and processing workloads for performance, scalability, and cost efficiency.

- Implement security, privacy, access control, and data governance throughout the data lifecycle.

- Monitor pipelines and platform components, troubleshoot failures, perform root-cause analysis, and implement corrective actions.

- Collaborate with architects, stakeholders, application teams, and QA/UAT teams to deliver solutions aligned with business objectives.

- Contribute to CI/CD, automation, reusable frameworks, development standards, mentoring, and continuous improvement initiatives.

Role Requirements :

- Strong proficiency in SQL, including complex queries, analytical functions, stored procedures, and performance optimization.

- Strong understanding and hands-on experience with modern data architecture, including Data Lake, Lakehouse, Cloud Data Warehouse, Medallion Architecture, and ELT patterns.

- Strong understanding of data warehousing and data modeling, including dimensional modeling, fact/dimension design, and Slowly Changing Dimensions (SCD).

- Hands-on experience with cloud data platforms and modern data engineering technologies.

- Experience working with relational and non-relational databases, data ingestion, and streaming technologies.

- Understanding of data quality, governance, security, and observability practices.

- Proficiency in Python, Shell, PowerShell, or equivalent scripting and automation technologies.

- Experience with Git, CI/CD, and Agile delivery practices.

- Excellent hands-on knowledge of dbt architecture, configuration, user setup, and administration.

- Strong experience integrating dbt with Amazon Redshift datasets and Azure DevOps (ADO) configurations.

- Strong understanding of security requirements for PII and PCI data.