Reports to: Lead Data Engineer 

• Create and maintain optimal data pipeline architecture ETL/ ELT into Structured data 
• Assemble large, complex data sets that meet functional / non-functional business requirements and create and maintain  multi-dimensional modeling like Star Schema and Snowflake Schema, normalization, de-normalization, and joining of datasets.
• Expert-level experience creating Fact tables, Dimensional tables, and ingesting datasets into Cloud-based tools. Job Scheduling  and automation experience is a must. 
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re designing infrastructure for greater scalability, etc.
• Set up and maintain data ingestion, streaming, scheduling, and job monitoring automation. Connectivity between the Data  factory, Blob storage, SQL, and 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 on Azure 
• 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 IT 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.

Required Skills: 

• Hands-on experience in data warehousing (Synapse or any OLAP) to support business/data analytics, business intelligence (BI)
• Advanced knowledge of SQL and experience working with relational databases, query authoring (SQL) as well as working  familiarity with a variety of databases and Cloud Data warehouses 
• Have a thorough understanding and experience in building and implementing scalable Machine Learning frameworks ready to  be consumed by Microservice Architecture.  
• Deep understanding of foundational math associated with machine learning such as linear algebra, numerical optimization,  probabilistic models, and statistics. 
• Data Model development, additional Dims and Facts creation, and creating views and procedures, enable programmability to  facilitate Automation 
• Experience in data compression to improve processing and finetuning SQL programming skills required
• 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 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
• Strong analytical and problem-solving skills to be able to structure and solve open-ended business problems (pharma  experience is highly preferred)

Experience: 4-8 years of professional work experience in data warehousing

Industry Type: Pharmaceutical

Education: Bachelor’s degree in Computer Science, Software or Computer Engineering

Location: Bangalore