Position: Senior Data Engineer Azure
Company: Unicsoft
Category: Data Engineer
Experience required: 5y
English level: intermediate

The The Client mission is to create a clear path to focus on optimal patient care for our healthcare partners by providing innovative, effective, and efficient technological solutions to overcome barriers in streamlining traditional workflow. With deep technical expertise, The Client is empowering enterprises to harness the full power of the cloud and emerging technologies such as blockchain, artificial intelligence, machine learning, and natural language processing through customized solutions and first-party cloud-based products. The Client is uniquely comprised of technologists and clinicians who share a deep understanding of medical market needs and the appropriate application of cloud technology + AI to solve the biggest burdens in healthcare. 



Position Responsibilities:



Data Integration
Using cloud technology, combine data from various sources, cloud/API/Other, based on requirements
Perform data cleansing and standardization
Load data into a cloud data warehouse as projects dictate
Using the enterprise ETL tool, create modify, and improve integration pipelines
Translate business requirements into data warehouse pipelines using ETL/ELT methodologies
Extract and load many disparate systems into a centralized data warehouse
Build/Maintain the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and CSP ‘big data’ technologies.
Business Intelligence & Data Analysis
Assist with preparing and loading data for Analysis and BI reports and dashboards
Identify opportunities for new data sources
Collaborate with analysts to come up with creative solutions to data challenges
General Responsibilities
Import and integrate new data sources based on business need
Proactively identify potential data problems, but react as needed to unexpected issues
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Handle multiple projects and meet deadlines
Monitor, schedule, and maintain existing integrations
Design tables, stored procedures, views, and other database objects within SQL Server, Aurora MySQL, Postgres.
Fully administer and maintain database environments to include: Business Continuity / Disaster Recovery Planning, Cost control, Performance Monitoring, Measuring and Reporting, 
Scaling and Data Resiliency Techniques 

Develop automated processes using ETL tools.
Analyze data and create sound database designs complete with documentation and data 
Dictionaries and data classifications.

Proven ability to successfully troubleshoot and improve database performance issues.
Develop and maintain SQL Test Scripts.
Work with team lead to track progress on projects and update tracking systems.
Use source control to track changes to the database.
Collaborate with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Responsible for the maintenance, creation and control of all personally identifiable information or any other information protected by any Confidentiality or Privacy Standards or Company policies that you have access or knowledge of, including but not limited to any state or federal regulations including HIPAA/HITRUST 
Assemble large, complex data sets that meet functional / non-functional business requirements
Ask smart questions, take risks and champion new ideas.


Requirements:



Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Proficiency in Python 
Three or more years’ experience creating and maintaining optimal data pipelines for SQL and NoSQL databases 
Three or more years’ experience working within the AWS/Azure ecosystem especially with the following: Azure File Storage, Azure Data Bricks, Azure DevOps, Azure Data Factory, Azure Data Lake, and Azure SQL  
Three or more years’ experience in data manipulation, algorithms, advanced math, and/or statistical modeling 
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.
A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
Experience with big data tools: Hadoop, Spark, Kafka, etc.
Experience with data pipeline and workflow management tools:   Azure Machine Learning, Azure Data Factory or other cloud equivalents
Be open to receiving feedback and constructive criticism.
Experience working with Data Warehouse solutions – Such as Snowflake