Data Engineer

About Us

dotSolved, headquartered in Silicon Valley USA, is a leading global provider of business process automation, modern application engineering, and cloud infrastructure services. dotSolved focuses on enabling digital transformations for small, medium, and large enterprises, in the following industries (but not limited to): High technology, Energy, Manufacturing, Financial Services, Media & Entertainment, Communications, Retail, Healthcare, and Education.dotSolved drives digital transformations for enterprises by defining, automating, and optimizing complex business processes for the digital era and engineering modern, data & analytic driven, applications that deliver intended business value. With hundreds of successful implementations and experience in Big Data, ERP, and Supply Chain, dotSolved can guarantee the creation of measurable business value from project engagements leading to accelerated business growth and profitability for customers.Data Engineer who can work on data lake system, which has been implemented on Databricks.

Required Skills

Must be proficient in the major languages such as Scala, Spark, and Kafka (any variant). Write elegant and maintainable code, and be comfortable with picking up new technologies.Proficient in working with distributed systems and have experience with different distributed processing frameworks that can handle data in batch and near real-time pipelines.Experience in working with AWS cloud services and Databricks (preferred) to build end-to-end data lakehouse solutions that bring different systems togetherCapability to understand and implement metadata-based data processing framework and methodologiesExperience in working with CICD process - Jenkins, & GIT ActionsExperience in working with monitoring and control stack - Prometheus/Grafana

Key Job Responsibilities

Drive the backbone of our organizational data platform by building robust pipelines that turn complex data into actionable insights using AWS and the Databricks platformDesign scalable, maintainable data systems with strong observabilityMonitor, log, alert, and ensure system robustnessBuild efficient pipelines for structured and unstructured dataInterface with Product engineering, regulatory, and legal teams as necessary to ensure Lakehouse’s compliance adherenceWrite clean, efficient code that handles massive amounts of structured and unstructured datacheck(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#1026E3;border-color:#1026E3;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered="">