Jobs at Nasstar

Entry-level data engineer to follow a structured 12-month development programme. Build internal reporting, reusable engineering frameworks, documentation, and tooling while learning SQL, Python, Databricks and cloud data services. Support senior engineers, join code reviews, shadow customer workshops, and progressively contribute to client projects.

Design, build and maintain cloud-native ETL/ELT pipelines and data lake solutions using dbt, Snowflake/Databricks and AWS services. Optimize SQL and data models for performance and cost, create dashboards, follow CI/CD and software engineering best practices, and collaborate with architects, engineers and clients to deliver production-ready enterprise data solutions.

Own Databricks-centric presales: lead discovery, design Lakehouse reference architectures, run demos/POCs, produce RFPs/SOWs, and align Sales, Delivery, and Databricks partner teams to win data engineering, MLOps, and GenAI deals.

Drive new logo acquisition (80%) and expand existing Nasstar accounts (20%) by leading consultative Microsoft Data & AI solution sales, collaborating with Microsoft sellers, managing end-to-end sales cycles, delivering presentations/demos, and executing go-to-market and account growth strategies.

Client-facing Principal Data Engineer leading design and delivery of enterprise Databricks-based data platforms. Provide architecture leadership, mentor engineering teams, drive platform optimisation, define standards, support technical governance, and deliver across multiple consultancy engagements.

Client-facing role designing, building, and maintaining scalable Azure cloud infrastructure and data platforms. Lead IaC implementations, CI/CD automation, container orchestration, security and governance, managed services, and mentor teams to deliver reliable cloud solutions.

Lead design and implementation of data governance and MDM strategies, develop policies and metadata/lineage practices, enforce data quality, deploy governance tooling, engage stakeholders, ensure regulatory compliance, and mentor team members.

Design, build, and deploy AI systems (predictive models, NLP, generative AI) from PoC to production. Work with clients to define use cases, prepare large datasets, implement deployment and monitoring pipelines using cloud-native tools, and collaborate with cross-functional teams to operationalize AI solutions.

Client-facing cloud engineer designing, building, and operating scalable AWS infrastructure and data-platform foundations. Lead IaC implementations, CI/CD automation, container orchestration, security and governance, managed services, technical presales, and mentor junior engineers.

Design, build, and maintain scalable cloud-based data platform and ETL pipelines on Azure. Develop data models, ensure data quality, optimize performance, implement governance and security, and collaborate with stakeholders and data scientists to enable data-driven solutions.