Responsibilities :
The following are responsibilities related to the Sr. Data Engineer
- Design and build a modern data warehouse in the cloud. Develops technical solutions to complex problems which require the regular use of ingenuity and creativity. Develop proof-of-concept (POC) solutions to help business units better visualize their business needs and to clarify requirements for development.
- Work with Business Technology Partners to understand business problems
- Provide recommendations to business via analytics consulting services
- Ingest data from all enterprise systems into a design that is fit for use
- Utilize cloud computing experience, knowledge and skills
- Utilize expertise in Microsoft Azure
- Utilize deep knowledge and skill in extract, transform, load (ETL) design, development, and performance tuning on Microsoft SSIS in SQL Server 2012 and above in a multi-dimensional Data Warehousing environment
- Data ingestion and modeling for digital customer platform
- Ingest data across safety assessment business related to customer platform
- Utilize methodologies in aggregating customer data from different applications, cleaning it, and analyzing it to get a reasonable picture of customer information and preferences
- Utilize experience with ADF, ADLS, Data Bricks and SQL
- Provide insights on data sets to business
- Perform ad-hoc analysis and present results in a clear and user-friendly manner. Perform testing, resolve issues and automate unit tests. Process, cleanse, and verify the integrity of data used for analysis.
- Conduct data profiling and cleansing as needed for each data source
- Build code using skills in advanced SQL Programming: PL/SQL, T-SQL, U-SQL, that automates data validation
- Review reports with results of data profiling on any new data source for business consumption
Job Qualifications
- Bachelor s degree in Computer Engineering, Computer Science or related discipline, Master s Degree preferred
- 7+ years of ETL design, development, and performance tuning on Microsoft SSIS in SQL Server 2012 and above (2016 preferable) in a multi-dimensional Data Warehousing environment
- 4+ years of SSAS design, development, maintenance and performance tuning on Microsoft SQL Server 2012 and above (2016 preferable), with expert MDX and DAX skills
- 7+ years of advanced SQL Programming: PL/SQL, T-SQL, U-SQL
- 4+ years of Enterprise Data & Analytics solution architecture
- 2+ years of Power BI experience including mobile solutions
- 2+ years of strong and extensive hands on experience in Azure, preferably data heavy / analytics applications leveraging relational and NoSQL databases, Data Warehouse and Big Data
- Experience with Azure Data Lake, Azure SQL Data Warehouse, Data Catalog, Azure Analysis Services, Data Bricks, Storage Account Gen2, Azure SQL Database, Azure DNS, Virtual Network, DocumentDB, Azure App Service, Data Factory
- Experience with Big Data Technologies such as: Hadoop, Sqoop, Hive, Kafka, Spark, Pyspark, Python, Scala or Pig
- Experience designing and building cloud native applications as well as Azure Cloud migration experience
- Experience with Azure IaaS and PaaS services
- Experience with Big Data Management (BDM) for relational and non-relational data (formats like json, xml, avro, parquet, copybook, etc.)
- PowerShell, Azure RunBook, and Azure DevOps experience
- Experience with setting up and operating data pipelines using Python or SQL
- Strong analytical abilities and a strong intellectual curiosity
- Self-starter with the ability to work independently or as part of a project team
- Capability to quickly conduct performance analysis, troubleshooting and remediation particularly in complex ETL mappings for SSAS
- Strong knowledge of emerging technologies and tools
- Strong organizational and time management skills
- Effective collaboration of tasks across the business and technical teams
- Proven and recent experience of implementing solutions from requirements gathering and process design to functional production deployment
- Demonstrated ability to produce high quality deliverables
- An equivalent combination of education and experience may be accepted as a satisfactory substitute for the specific education and experience listed above
Preferred Skills:
- Hands on experience with data virtualization technologies: CIS (Tibco), Denodo, or SQL 2019 Virtualization
- Experience working with other public cloud technologies AWS, GCP
- Excellent ability to communicate complex quantitative analysis in a clear, precise, and actionable manner with both technical and business stakeholders
- Experience building test automation to ensure data quality and accuracy
- Experience with any of the following scripting languages, R, SAS, JavaScript, Regex, PowerShell, shell scripting
- Experience working in data and analytics in the Life Sciences industry