Core Responsibilities

• Create structured data and maintain optimal data pipeline architecture ETL/ ELT

• Assemble large, complex data sets that meet business requirements and create and maintain Multi-Dimensional modelling like Star Schema and Snowflake Schema, normalization, de-normalization, joining of datasets.

• Expert level experience creating Fact tables, Dimensional tables and ingest datasets into Cloud based tools. Job Scheduling, automation experience is must.

• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

• Setup and maintain data ingestion, streaming, scheduling and job monitoring automation. Connectivity between Lambda, Glue, S3, Redshift, Power BI needs to be maintained for uninterrupted automation.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data technologies like AWS and Google

• Build analytics tools that utilize the data pipeline to provide actionable insight into customer acquisition, operational efficiency, and other key business performance metrics

• Work with cross-functional teams including external consultants and IDS business partners to provide technical guidance and review

• Create data tools for analytics and data science that assists in building and optimizing products that become industry leader

Required

• 4-6 years of in-depth hands-on experience in data warehousing Redshift or any OLAP to support business/data analytics, business intelligence (BI). Experience with Redshift and OLAP systems is must along with GLUE pipeline skills

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases and Cloud Data warehouse like Redshift

• Data Model development, additional Dims and Facts creation and creating views and procedures, enable programmability to facilitate Automation

• Prior Data Modelling, OLAP cube modelling in SQL Server, SSAS and Power BI experience

• Data compression into PARQUET to improve processing and finetuning SQL programming skills required

• Experience of building and optimizing big data data pipelines, architectures and data sets

• Experience of 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 structured and unstructured datasets

• Experience with manipulating, processing, and extracting value from large unrelated datasets

• Working knowledge of message queuing, stream processing, and highly scalable big data stores

• Experience of collaborating with cross functional teams including external consultants, globalIDS and analytics teams

Preferred Qualifications/Expertise

• Experience with relational SQL and NoSQL databases, including AWS Redshift

• Experience with AWS cloud services Preferable: S3, Lambda, Glue, Redshift

• Experience with stream-processing systems: Storm, Spark-Streaming, etc.

• Experience with object-oriented/object function scripting languages: Python, Java, R, C++ Scala, etc.

• Experience working on Medical/ Sales/ RWE data sources. For e.g. APLD, Premier, Flatiron, Optum, IBM Marketscan (Truven)

• Latest relevant certification courses would be a bonus

• Strong analytical skills coupled with an ability to think strategically in an ambiguous environment

• High level of motivation and a strong desire to find creative solutions to challenging situations. Ability to work across teams and build TeamLilly culture

Education:

• Bachelor s or master s degree on Technology and Computer Science background