Eisai US

Assoc Director, Commercial, Omni Channel

Bayer

Sr Analytics Lead - Consumer Health, Commercial Ops, North America

Daugherty Business Solutions

Lead and support various fortune 500 clients with data strategy, visualization, kick start data initiatives and solutioning for the most critical business problems.

Data Solutions Lead

Asembia

► Hired to drive data transformation, modernize and upgrade legacy technology stack, improve process efficiencies, perform P&L analysis, provide strategic vision and direction for teams.

► Established a newly formed data analytics team, overseeing data management and analytics on behalf of the company’s Healthcare clients.

► Named as a Finalist of the Women in IT Awards 2018 (USA) in the Data Leader of the Year category.

Director, Enterprise Data Solutions and Strategy

Delta Dental of New Jersey and Connecticut

► Founded an in-house software development function for the New Jersey unit. Formed an Agile/Scrum development team, trained on Agile software delivery and release practices, and managed multiple concurrent projects.

► Lowered costs and improved strategic partnerships by examining outsourced vendor relationships supporting enterprise claims processing.

Product Manager

IMS Health

► Responsible for leading inhouse and outsourced data operations teams, directing projects to build business intelligence dashboards, data visualizations, and related analytics for large volumes of data. 

► Projects included the administration of the end-to-end SDLC budget of a $2MM formulary data project. Excessive knowledge of IMS data sets like Xponent, PlanTrak and FIA.

Sr Manager, Managed Care Analytics

CSG International

► Led the development of cost-effective solutions in accordance with Agile methodologies, working as a liaison between business and technical teams.

Technical Lead/ Product Owner

Leading Data Teams | Public Speaker | Author of "Thriving in a Data World" Book | Healthcare and CPG Data Strategies | Transforming Numbers into Compelling Stories

Data Analytics Leader with extensive experience in big data analytics, product management, software development engineering and cross functional team leadership. Skillfully leverage blend of business, data and technical knowledge to solve complex business problems and develop data products to automate workflows, improve accuracy and generate cost savings.

Established data analytics teams from the ground up to offer self service reporting and grow profitability of data solutions.

Recognized as a Finalist of the Women in IT Awards 2018 (USA) in the Data Leader of the Year category.

Notable Specialties and Experience:

•	Data Strategy and Big Data Analytics
•	Product Management
•	Business Intelligence and Visualization 
•	Team Leadership 
•	Manage P&L
•	Healthcare, Life Sciences, Supply Chain, Insurance and Billing 
•	AWS and other cloud products
•	Operational excellence
•	Vendor Management
•	Data technologies and Coding 
•	Speaker
•	Book author 
•	Content writer

Sangeeta Krishnan

Confidential

Senior Data Engineer

Kockpit Analytics

Business Intelligence Developer

Lushai Analytics

BI Analyst

Mizoram University

Junior Project Manager - Database and Visualization

Developer - Database and Visualization

Hi, I am a Data Engineer with experience in both the field of Data Analytics and Data Engineering.

➡️ Tech stack I worked so far : SQL, Power BI, Python, Apach Spark (Pyspark), Azure Cloud Service (ADF, ADLS-Gen2, Databricks, Azure Functionapp, Azure Webapp, etc), Snowflake Data Warehouse, Flask and Quart web development framework.

➡️ Worked on both on-prem as well as cloud technologies.

➡️ Experience with providing end-to-end data solutions started from building the ETL architecture to Power BI development and implementation as well as creating websites/applications on Flask and Quart framework.

➡️ Domains I worked so far: Retail, FMCG, Energy and Utilities and E-commerce.

➡️ Worked with clients from India, US and UK.

➡️ Closely worked with C-level management professionals for providing the best fit solutions by understanding the business requirements.

➡️ A team player and an individual contributor with experience of working in Agile methodology and Scrum framework.

Munna Das

SQL sub queries can be very confusing to a beginner.

As a beginner I also had a hard time understanding and writing sub queries.

Here's an approach that helped me a lot during my initial days with SQL :

➡️ Read the problem statement multiple time and note down what are the fields/insights the problem statement is demanding.

➡️ Do not focus on sub-queries initially but just treat the sub-query as an individual query and note down all the queries required to achieve the objective. You don't necessarily have to write it correctly but just for basic understanding of what you are trying to find.

➡️ Out of all the queries you wrote above, find out which one is the innermost query, the one which is independent of all the other queries and can be calculated directly from the dataset.

➡️ Write this independent query first, then find out that query which is directly dependent on this query and check on how you can integrate both these query together.

➡️ Likewise keep on identifying the next dependent query and keep on integrating.

Here's a simple example for better understanding:

📍Problem statement: Find the name of employees in a company whose salary is above the average salary of their development.

➡️ Here we need to find two things:
📍 employee who's salary is greater than average salary of his department
📍 average salary of the departments.


➡️ First query depends on the 2nd query and 2nd query is independent. So write down the 2nd query first :

📍 SELECT dept_id, avg(salary) AS avg_salary From employees GROUP BY dept_id

➡️ Understanding the logic behind the dependent query :

📍rough query : SELECT employee_name FROM employee WHERE salary > the answer that you are getting from the above query.

➡️ Understanding how to integrate both this query together to get the correct answer based on the employee's department and you are done ✅

P.S - Even if the person prefers CTE, they can use the above approach to understand how to create CTE and integrate it with the main query.

#sql #data

Senior AI Engineer | Backend Engineer | Agentic AI | Generative AI

Working extensively on Azure helped me realize that though there are so many services azure offers, these are the services a Data Engineer will work with 80-90% of the time :

📍 ADF: Creating pipelines for the ETL process.
📍 ADLS: Data Lake for storing the data.
📍 Azure Function: serverless compute service for running event-driven code.
📍 Azure SQL DB: Relational Database.
📍 Azure Cosmos DB : NoSQL Database.
📍 Azure Synapse: Analytics and Data Warehousing.
📍 Azure DevOps: CI/CD and DevOps
📍 Azure Key Vault: Managing secrets and keys.
📍 Azure Databricks: Unified platform for data, analytics and Al.

Rest 10-20% may vary based on the project requirements.

#azure #dataengineer #sql #data

taplio

The Battle

Sangeeta Krishnan

Munna Das

Followers

Posts

Engagements

Likes

Performance ScoreMunna Das's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Sangeeta Krishnan

Munna Das

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Munna Das's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreMunna Das's LinkedIn Performance