Senior Data Engineer

Company Description DVK Analytics is a certified Sisense reseller and implementation partner that helps organizations transform how they build, use, and scale analytics. The company delivers next-generation Sisense solutions by combining expert BI consulting with proprietary products such as advanced plugins, AI-driven capabilities, and enhanced dashboard experiences. DVK Analytics supports enterprises across industries including Retail, Renewable Energy, Healthcare, and E-commerce, enabling them to modernize analytics, improve decision-making, and increase operational efficiency. By building scalable data models, creating impactful dashboards, and integrating AI for natural-language insights, DVK Analytics empowers teams to move beyond traditional BI approaches. The organization focuses on elevating the analytics experience for clients who use or plan to use Sisense.
Role Description The Senior Data Engineer role is a full-time remote position responsible for designing, building, and maintaining scalable data pipelines and architectures that power advanced analytics and BI solutions. Day-to-day responsibilities include developing robust ETL processes, optimizing data models for Sisense, and implementing data warehousing best practices to support performant reporting and dashboards. The role involves close collaboration with BI consultants, data analysts, and product teams to translate business requirements into reliable data solutions, as well as troubleshooting data issues and improving data quality and reliability. The Senior Data Engineer will contribute to architecture decisions, mentor junior team members, and help integrate modern data tools and cloud platforms to support DVK Analytics’ next-generation analytics offerings.
Qualifications
Strong data engineering skills, including experience designing and maintaining scalable data pipelines and architectures.
Proficiency in data modeling and data warehousing to support analytics, reporting, and BI tools such as Sisense.
Hands-on expertise with Extract Transform Load (ETL) processes and tools, ensuring reliable data ingestion, transformation, and integration.
Solid data analytics capabilities to interpret requirements, validate data outputs, and collaborate effectively with BI and analytics teams.
Experience with SQL and at least one programming language commonly used in data engineering (e.g., Python, Java, or Scala).
Background working with cloud data platforms (e.g., AWS, Azure, or GCP), including managed databases and data pipeline services.
Familiarity with BI platforms, ideally Sisense, and an understanding of how data structures impact dashboard performance and user experience.
Strong problem-solving skills, attention to detail, and the ability to work independently in a remote, collaborative environment.
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.

Work arrangement
Yes