General Responsibilities
- This role is responsible for designing developing maintaining and optimizing ETL (Extract Transform Load) processes in Databricks for data warehousing data lakes and analytics.
- The developer will work closely with data architects and business teams to ensure the efficient transformation and movement of data to meet business needs including handling Change Data Capture (CDC) and streaming data.
Tools used are :
Azure Databricks Delta Lake Delta Live Tables and Spark to process structured and unstructured data.Azure Databricks / PySpark (good Python / PySpark knowledge required) to build transformations of raw data into curated zone in the data lake.Azure Databricks / PySpark / SQL (good SQL knowledge required) to develop and / or troubleshoot transformations of curated data into FHIR.Data design
Understand the requirements. Recommend changes to models to support ETL design.Define primary keys indexing strategies and relationships that enhance data integrity and performance across layers.Define the initial schemas for each data layerAssist with data modelling and updates of sourcetotarget mapping documentationDocument and implement schema validation rules to ensure incoming data conforms to expected formats and standardsDesign data quality checks within the pipeline to catch inconsistencies missing values or errors early in the process.Proactively communicate with business and IT experts on any changes required to conceptual logical and physical models communicate and review timelines dependencies and risks.Development of ETL strategy and solution for different sets of data modulesUnderstand the Tables and Relationships in the data model.Create low level design documents and test cases for ETL development.Implement errorcatching logging retry mechanisms and handling data anomalies.Create the workflows and pipeline designDevelopment and testing of data pipelines with Incremental and Full Load.Develop high quality ETL mappings / scripts / notebooksDevelop and maintain pipeline from Oracle data source to Azure Delta Lakes and FHIRPerform unit testingEnsure performance monitoring and improvementPerformance review data consistency checksTroubleshoot performance issues ETL issues log activity for each pipeline and transformation.Review and optimize overall ETL performance.Endtoend integrated testing for Full Load and Incremental LoadPlan for Go Live Production Deployment.Create production deployment steps.Configure parameters scripts for go live. Test and review the instructions.Create release documents and help build and deploy code across servers.Go Live Support and Review after Go Live.Review existing ETL process tools and provide recommendation on improving performance and reduce ETL timelines.Review infrastructure and remediate issues for overall process improvementKnowledge Transfer to Ministry staff development of documentation on the work completed.Document work and share the ETL endtoend design troubleshooting steps configuration and scripts review.Transfer documents scripts and review of documents to Ministry.Requirements
Must Have Skills
7 years using ETL tools such as Microsoft SSIS stored procedures TSQL2 Delta Lake Databricks and Azure Databricks pipelines
Strong knowledge of Delta Lake for data management and optimization.
Familiarity with Databricks Workflows for scheduling and orchestrating tasks.2 years Python and PySparkSolid understanding of the Medallion Architecture (Bronze Silver Gold) and experience implementing it in production environments.Handson experience with CDC tools (e.g. GoldenGate) for managing realtime data.SQL Server OracleExperience :
Experience of 7 years of working with SQL Server TSQL Oracle PL / SQL development or similar relational databasesExperience of 2 years of working with Azure Data Factory Databricks and Python developmentExperience building data ingestion and change data capture using Oracle Golden GateExperience in designing developing and implementing ETL pipelines using Databricks and related tools to ingest transform and store largescale datasetsExperience in leveraging Databricks Delta Lake Delta Live Tables and Spark to process structured and unstructured data.Experience working with building databases data warehouses and working with delta and full loadsExperience on Data modeling and tools e.g. SAP Power Designer Visio or similarExperience working with SQL Server SSIS or other ETL tools solid knowledge and experience with SQL scriptingExperience developing in an Agile environmentUnderstanding data warehouse architecture with a delta lakeAbility to analyze design develop test and document ETL pipelines from detailed and highlevel specifications and assist in troubleshooting.Ability to utilize SQL to perform DDL tasks and complex queriesGood knowledge of database performance optimization techniquesAbility to assist in the requirements analysis and subsequent developmentsAbility to conduct unit testing and assist in test preparations to ensure data integrityWork closely with Designers Business Analysts and other DevelopersLiaise with Project Managers Quality Assurance Analysts and Business Intelligence ConsultantsDesign and implement technical enhancements of Data Warehouse as required.Development Database and ETL experience
Experience in developing and managing ETL pipelines jobs and workflows in Databricks.Deep understanding of Delta Lake for building data lakes and managing ACID transactions schema evolution and data versioning.Experience automating ETL pipelines using Delta Live Tables including handling Change Data Capture (CDC) for incremental data loads.Proficient in structuring data pipelines with the Medallion Architecture to scale data pipelines and ensure data quality.Handson experience developing streaming tables in Databricks using Structured Streaming and readStream to handle realtime data.Expertise in integrating CDC tools like GoldenGate or Debezium for processing incremental updates and managing realtime data ingestion.Experience using Unity Catalog to manage data governance access control and ensure compliance.Skilled in managing clusters jobs autoscaling monitoring and performance optimization in Databricks environments.Knowledge of using Databricks Autoloader for efficient batch and realtime data ingestion.Experience with data governance best practices including implementing security policies access control and auditing with Unity Catalog.Proficient in creating and managing Databricks Workflows to orchestrate job dependencies and schedule tasks.Strong knowledge of Python PySpark and SQL for data manipulation and transformation.Experience integrating Databricks with cloud storage solutions such as Azure Blob Storage AWS S3 or Google Cloud Storage.Familiarity with external orchestration tools like Azure Data FactoryImplementing logical and physical data modelsKnowledge of FHIR is an assetDesign Documentation and Analysis Skills
Demonstrated experience in creating design documentation such as :
Schema definitions
Error handling and loggingETL Process DocumentationJob Scheduling and Dependency ManagementData Quality and Validation ChecksPerformance Optimization and Scalability PlansTroubleshooting GuidesData LineageSecurity and Access Control Policies applied within ETLExperience in FitGap analysis system use case reviews requirements reviews coding exercises and reviews.Participate in defect fixing testing support and development activities for ETLAnalyze and document solution complexity and interdependencies including providing support for data validation.Strong analytical skills for troubleshooting problemsolving and ensuring data quality.Certifications
Certified in one or more of the following certifications :
Databricks Certified Data Engineer AssociateDatabricks Certified Professional Data EngineerMicrosoft Certified : Azure Data Engineer AssociateAWS Certified Data Analytics SpecialtyGoogle Cloud Professional Data EngineerCommunication Leadership Skills and Knowledge Transfer
Ability to collaborate effectively with crossfunctional teams and communicate complex technical concepts to nontechnical stakeholders.Strong problemsolving skills and experience working in an Agile or Scrum environment.Ability to provide technical guidance and support to other team members on Databricks best practices.Must have previous work experience in conducting Knowledge Transfer sessions ensuring the resources will receive the required knowledge to support the system.Must develop documentation and materials as part of a review and knowledge transfer to other members.