Role and Responsibilities

• Create and maintain optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL server and Azure big data technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Great adaptability to the technology change and capability to design advanced Data Architectures
• Support software developers, database architects, data analysts and data scientists on data initiatives and ensure optimal data delivery architecture throughout projects.

Essential Skills and Qualifications:

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Mandatory experience in one of the programming languages - Python or Java
• Experience building and optimizing big data data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• Working knowledge of message queuing, stream processing, and highly scalable big data data stores.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Experience in building Data-Ingestion and ETL/ELT Pipelines
• Overall, 8 years of experience, should have experience using the following software/tools:
• Strong working experience in Azure Cloud offerings especially for data engineering work (Azure data lake, Azure Data factory, data bricks, azure SQL)
• Experience with storage formats - Parquet, Avro
• Experience with API authentication and endpoint consumption
• Experience with data pipeline and workflow management tools
• Must have: Experience with big data tools: Spark, Python, Azure Cloud, Power BI.
• Preferred Healthcare domain knowledge
• Hands-on working experience in Linux & Windows environment
• Hands-on working experience in bash scripting
• Good to have: Experience in stream processing architecture.
• Good to have: Experience in Webapp Development (C#, API development)