Databricks Specialist

We are looking for an experienced Databricks Specialist to build, run and maintain data pipelines and curated data products on an enterprise Azure Data Lake that supports business-critical reporting. The role covers the full path from raw data to trusted, reusable Delta tables: developing Databricks jobs, choosing the right load method, managing downstream impact on dependent use cases, and resolving failures in a live production environment. The specialist will work closely with business data product owners, use case teams and platform engineers, under ticket-based change control and disciplined documentation. Department: Managed Service Employment Type: Full-time Experience: 1-3 Years Workplace Type: On-site Number of Vacancies: 2 Location: Dhaka Deadline: 31 Oct 2026 Key Responsibilities 1.1 Data Product DevelopmentDesign, build and maintain Databricks jobs (PySpark and SQL) that turn raw landed data into curated, trusted Delta tables.Select and implement the right load method for each data product: full refresh, SCD Type 1 (overwrite) or SCD Type 2 (historized).Build new data products end to end when new sources are approved: ingestion hand-off, processing, scheduling, alerting and documentation.Extend existing data products with new columns, tables or source data, and remove data that is no longer required.1.2 Pipeline Operations and ReliabilityMonitor scheduled jobs, investigate failures and anomalies, and trace issues back through the data layers to their root cause.Reprocess historical data from the raw layer when a fix must apply to pastWork with Azure Data Factory pipelines and Azure Data Lake Storage Gen2 to keep ingestion and processing aligned.Support incident recovery and root-cause analysis, and document permanent fixes for recurring issues.1.3 Downstream Impact and Use Case SupportMaintain the dependency map between data products and the use cases that consume them, and check every change against it before release.Make data available to use case teams, answer technical questions on data content and load logic, and support them as they build.Read and explain existing transformation code to business stakeholders, and apply logic changes only on the business owner's instruction.1.4 Performance and Cost OptimizationTune job schedules, run times, cluster configuration and compute cost to meet businessMaintain data product workspaces, clusters, repositories andRecommend optimization opportunities (e.g. cluster rightsizing, incremental processing) with expected benefit.1.5 Governance, Documentation and CollaborationWork through ticket-based change control on Azure DevOps, recording requirements, decisions and outcomes on each ticket.Document every data product, change and fix so that the platform remains traceable andCollaborate with data engineers, BI analysts, platform administrators and business stakeholders in sprint-based delivery. Required Skills & Experience 1.1 Technical Skills5+ years of data engineering experience, including hands-on production work in AzureStrong Apache Spark (PySpark) and SQL skills, with experience building and optimizing Delta Lake tables.Practical experience with load patterns including full refresh, SCD Type 1 and SCD TypeWorking knowledge of Azure Data Factory, Azure Data Lake Storage Gen2 and the Azure data platform.Experience with Databricks workflows, clusters, repositories and job scheduling, including performance and cost tuning.Familiarity with Git-based source control and CI/CD (Azure DevOps or GitHub).Strong debugging skills across multi-layer data platforms (raw, curated and consumption layers).1.2 Professional CompetenciesBuild-and-run mindset: comfortable owning both new development and day-to-day production stability.Careful, impact-aware approach to change in a shared platform where one data product feeds many consumers.Clear communicator who can explain data logic and technical issues to businessStructured working style with disciplined documentation and change-controlAble to work effectively with remote, international stakeholders and multiple dependent.1.3 Preferred QualificationsExperience operating an enterprise Data Lake in the automotive, manufacturing or logisticsFamiliarity with Python-based data quality checks, Airflow orExposure to Power BI or other BI tools consuming Databricks dataMicrosoft or Databricks certifications (e.g. DP-203, DP-600 or Databricks Data Engineer Associate/Professional). Interview Steps Technical/Functional InterviewHR InterviewOffer Apply Now Department: Managed Service Employment Type: FullTime Experience: 5+ Years Workplace Type: On-site Number of Vacancies: 1 Location: Dhaka Deadline: 30 Nov 2026 Apply Now