Senior Data Engineer

About the RoleAre you an experienced Data Engineer with deep expertise in Databricks and a strong track record of building and operationalizing modern data platforms? Our mission is to help customers transform their data into business value through highly scalable architectures, robust data engineering pipelines, reliable data consumption layers, and production-ready AI and machine learning solutions. As a Senior Data Engineer, you will play a critical role in this customer journey. You will work closely with internal teams and customers to design, build, deploy, and optimize data solutions that capture, transform, manage, and utilize data to support AI, machine learning, analytics, and business intelligence. The organization is a fast-growing technology startup expanding its operations in Nepal. Less than two years after its founding in the United States, it has established teams across LATAM, including Uruguay, Argentina, and Mexico. This is an excellent opportunity for an experienced Data Engineer to join the founding team in Nepal and work on technically challenging, customer-focused data projects. Critical Experience RequirementDatabricks experience is required for this position. Must Have: Minimum 5 years of hands-on Databricks experience. This is non-negotiable. Ideal: 7+ years of hands-on Databricks experience. Candidates without at least 5 years of professional Databricks experience will not be considered. The Impact You Will HaveSupport new and existing customers with their data engineering requirements. Work directly with customers to understand their data challenges and recommend appropriate technical solutions. Guide customers in making sound architectural and technical decisions. Design, build, deploy, and operationalize complex data solutions using modern data engineering technologies. Develop and maintain scalable Databricks-based data engineering pipelines and solutions. Work across multiple customer accounts while tracking project progress, delivery, and technical outcomes. Analyze data sources to assess quality, value, structure, and suitability for analytical and machine learning use cases. Design and implement data transformations, data processing workflows, and data quality solutions. Troubleshoot and resolve data pipeline, system, and production issues. Apply data governance, security, quality, and management best practices. Collaborate with engineering, data science, analytics, and other internal teams to deliver customer solutions. Support and educate end users on data products, platforms, and analytical environments. Perform data and system analysis, assessment, testing, and resolution of defects and incidents. Test data movement, transformation logic, pipelines, and other data components. Contribute to technical best practices, documentation, knowledge sharing, and continuous improvement. Must-Have QualificationsDatabricksMinimum 5 years of professional, hands-on experience with Databricks. Strong practical experience designing, developing, and operationalizing data engineering solutions using Databricks. Experience working with Databricks in production environments. 7+ years of Databricks experience is considered ideal. Data EngineeringStrong experience with modern data engineering technologies such as Apache Spark, Hadoop, Kafka, or similar technologies. Strong SQL skills and understanding of data warehousing concepts, including OLTP, OLAP, and analytical data platforms. Strong understanding of end-to-end data engineering and analytics workflows. Experience designing and implementing scalable data pipelines and data transformation processes. Strong data quality, governance, security, and data management fundamentals. Demonstrated ability to understand complex technical systems and translate business requirements into technical solutions. Strong problem-solving, debugging, and troubleshooting capabilities. Customer & Communication SkillsStrong English verbal and written communication skills. Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders. Experience working directly with customers or cross-functional stakeholders is highly desirable. Ability to manage priorities and deliver across multiple customer accounts or projects. Strong ownership, self-motivation, and ability to work independently. Working RequirementsAvailability to overlap with US working hours for up to 50% of the working day. Strong time management and prioritization skills. Demonstrated ability to continuously learn and adapt to evolving data technologies. Nice to HaveExperience with public cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP). Experience with data science and machine learning tools such as pandas, scikit-learn, or hyperparameter optimization (HPO). Experience supporting AI/ML workloads on Databricks. Databricks Data Engineer or Machine Learning certification. Experience with modern data transformation and orchestration technologies. Previous consulting, professional services, or customer-facing data engineering experience. Experience leading or mentoring other engineers. EducationBachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Technology, or a related technical field. Our Commitment to Diversity and InclusionWe are committed to fostering a diverse and inclusive culture where everyone can perform at their best. Hiring decisions are made in line with equal employment opportunity principles. Candidates are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical or mental ability, political affiliation, race, religion, sexual orientation, socio-economic background, veteran status, or any other protected characteristic. Why Join Us?Innovative Environment: Work with modern data engineering, AI, and analytics technologies. Customer Impact: Work directly on data challenges that influence real business outcomes. Global Exposure: Collaborate with teams and customers across the US and LATAM. Founding Team Opportunity: Join the growing Nepal team at an early stage and help shape its technical culture. Technical Growth: Work alongside experienced data engineering and technology leaders on complex data projects.