Job Description

JD:

Overall Responsibility:

Responsible for developing, implementing, and operating stable, scalable, low cost solutions to source data from client systems into the Data Lake, data warehouse and end-user facing BI applications. Responsible for ingestion, transformation and integration of data to provide a platform that supports data analysis and enrichment as well as making data operationally available for analysis. The data Engineer will be a data pipeline builder, data wrangler and support application developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture and is consistent throughout our ongoing projects.

Essential Functions:

• Build and maintain scalable automated data pipelines. Support critical data pipelines with a highly scalable distributed architecture-including data ingestion (streaming, events and batch), data integration, data curation.
• Having knowledge on Salesforce API to pull datafrom salesforce systemto Databricks Delta tables.
• Need to build scalable and metadata driven framework to reuse notebooks/pipelines to move data from salesforce to Databricks.Solution should work for future ingestions from salesforce to Databricks data movement with minimal changes.
• Deploy, automate, maintain and manage Azure cloud-based production system, to ensure the availability, performance, scalability and security of productions systems. Good architectural understanding to build and ensure customer success when building new solutions and migrating existing data applications on Azure platform. Conduct full technical discovery, identifying pain points, business and technical requirements, "as is" and "to be" scenarios.
• Design and arrangement of scalable, highly attainable, and fault tolerant systems on Azure platform.
• Ownership and responsibility for end-to-end design and development, testing, release of key components.
• Understand and implement best practices in management of data, including master data, reference data, metadata, data quality and lineage. Experience with code versioning tools and a command of configuration management concepts and tools, CI-CD including DevOps. Other duties as assigned.

Experience:

• Expert level SQL knowledge and experience.
• Experience with Azure cloud architecture and solutions.
• Experience with Azure Data lake store, Blob Storage, VMs, Data Factory, SQL Data Warehouse, Azure Databricks, HDInsight, etc. Expert level experience with Python/Pyspark/Scala and Object Oriented programming.
• Experience with streaming integration and cloud-based data processing systems such as; Kafka, and Databricks.
• Experience with healthcare data modeling standards, such as HL7 or FHIR is Mandatory.
• Experience in processing healthcare data sets (medical records, claims, clinical data etc.) is Mandatory.
• Hands-on knowledge of cloud-based data warehouse solutions like Azure & Snowflake.
• Experience with data pipeline and workflow management tools: Azure Data Factory, Airflow, etc.
• Experience with Oracle, Microsoft SQL Server Database system.
• Experience working within Agile methodologies.
• Experience with Microsoft Windows and Linux virtual servers. Moderate skill in Power BI .

Other Skills:

• Strong project management skills.
• Strong problem-solving, decision-making and analytical skills.
• Excellent interpersonal and organizational skills a team player who can effectively partner with all levels of the company.
• Detail oriented and organized.
• Ability to handle numerous assignments simultaneously.
• Ability to work independently and as part of a team.

Requirements.

• Minimum Education/Experience:
• Bachelor's degree (BA or BS) from an accredited college or university plus a minimum of six (6) years of experience in the specific or related field.

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