Jobs at SunnyData

Lead product vision, strategy, and roadmap for Ad Tech data and AI products. Partner with engineering and cross-functional teams to manage full software lifecycle, prioritize features, support triage and bug resolution, and deliver customer-centric API-first, data-driven solutions while driving business impact and operational excellence.

Lead product vision, strategy, and roadmap for an Ad Tech data platform. Partner with engineering and cross-functional teams to drive products from concept to launch, manage stakeholder communication, support triage/bug resolution, and prioritize data-driven, API-first solutions to deliver business impact.

Designs and executes manual and automated tests for data-driven applications, APIs, databases, and data pipelines. Develops test plans, regression tests, and automation; validates data accuracy and integrity; tracks defects; collaborates with engineering, data teams, and stakeholders; documents testing standards; and uses AI tools to improve test coverage and efficiency.

The QA Engineer translates requirements into test plans and cases, executes regression and automated testing, tracks defects, and validates fixes. The role focuses on data quality across applications, APIs, databases, and pipelines, while collaborating with engineering, data teams, and stakeholders. Responsibilities include establishing testing standards, improving automation and coverage, documenting results, troubleshooting defects, and using AI tools to improve testing efficiency.

Develop and execute manual and automated tests for data-driven applications, APIs, databases, and data pipelines. Translate requirements into test plans, validate data accuracy and integrity, track defects, and collaborate with engineering and business stakeholders. Establish testing standards, improve automation and coverage, and use AI tools to enhance testing efficiency and data validation.

Develop and execute manual and automated tests for data-focused applications, APIs, databases, and pipelines. Translate requirements into test plans, validate data quality and integrity, track defects, collaborate with engineering and stakeholders, and improve testing processes, automation, coverage, and efficiency using AI tools.

Lead the design, development, and production deployment of machine learning models and predictive analytics pipelines. Collaborate with engineering, product, analytics, and data teams to optimize cloud-based data solutions, automate workflows, and apply statistical modeling to business challenges. Mentor junior data scientists, establish MLOps best practices, and communicate insights and recommendations to stakeholders and executives.

Leads the design, development, deployment, and operationalization of machine learning models and predictive analytics pipelines. Works with large datasets, data engineers, and cross-functional teams to build cloud-based solutions, automate workflows, and apply statistical modeling. Mentors junior data scientists, communicates recommendations to stakeholders, and contributes to MLOps and model-development best practices.

Lead the design, development, deployment, and operationalization of machine learning models and predictive analytics pipelines. Collaborate with engineering, product, analytics, and data engineering teams to build scalable cloud-based data solutions, automate workflows, and translate business challenges into data-driven recommendations. Mentor junior data scientists, establish best practices, and communicate findings to stakeholders and executives.

Collaborates with clients to define business needs, designs data and business architectures, identifies data and AI opportunities, and translates requirements into technical specifications. Leads workshops, gap analyses, stakeholder alignment, governance improvements, and solution implementation. Develops delivery frameworks and accelerators while supporting client relationship growth and quantifying business value and ROI.

Collaborates with clients to define business needs, design data and business architectures, identify AI and analytics opportunities, and translate strategy into technical requirements. Leads workshops, gap analyses, stakeholder alignment, and solution implementation while improving data governance and delivery practices. Develops reusable frameworks, quantifies business value, and supports client relationship expansion.

Consults with clients to define business needs, design data-driven architectures, identify AI and process-improvement opportunities, and translate strategy into technical requirements. Leads workshops, aligns stakeholders, supports implementation teams, develops delivery frameworks, and helps expand client relationships. The role requires strong SQL, visualization, data governance, analytics, client-facing consulting, stakeholder management, and business analysis expertise.

Source, engage, assess, and hire technology candidates across the full recruitment lifecycle. Manage high-volume hiring for roles such as data engineers, data scientists, and solutions architects while delivering a strong candidate experience. Support Nepal people operations, including onboarding, offboarding, HR support, culture, and engagement initiatives. Collaborate in a fast-paced startup environment and stay current with technology trends and recruiting strategies.

Design, build, deploy, and operationalize scalable data engineering solutions for customers. Responsibilities include developing pipelines, transforming and cleansing data, analyzing sources, implementing governance, security, and quality practices, testing data movement and transformation code, resolving defects and incidents, and advising customers on technical decisions. The role also supports AI, machine learning, business intelligence, and data product adoption while collaborating across teams and educating end users.

As a Solutions Architect, guide customer data architecture needs, design and implement data solutions on Databricks, manage multiple accounts, and collaborate with sales teams while ensuring data governance and quality.

Design, build, and operationalize scalable data solutions for customers; support data ingestion, transformation, quality, governance, and analytics to enable AI/ML and BI. Troubleshoot, test pipelines, collaborate with teams, and guide customers on technical decisions.

Design and deploy end-to-end data architectures on Databricks, split between billable delivery and pre-sales; lead client engagements, mentor teams, manage accounts, ensure data governance, quality, security, and production readiness, and deliver technical documentation and presentations.

Design and implement Databricks-centered data architectures and pipelines, support pre-sales technical efforts, lead client engagements, mentor teams, ensure data governance/security, and deliver production-ready ETL/ML solutions.

As a Senior Data Engineer, you will design and deploy data solutions, enhance data quality, and collaborate with customers and teams to support data engineering needs.

Design, build, and operationalize complex data solutions for customers. Support data ingestion, transformation, cleansing, governance, and testing. Collaborate across teams, troubleshoot data incidents, guide technical decisions, and enable AI/ML and BI workloads while tracking customer account progress.