Experience

Defining the overarching structure of data management at the organization, the Data Governance Council and other roles and responsibilities

Defining how data is classified into levels of sensitivity, for example public data, internal data, classified data and restricted data.

Implementation of data cataloging tool to enforce data governance within the organization in Data Mesh.

Defining pipelines standard by creating different blueprint which helps any team to go live faster. Reduces go-live time in Data Mesh approach.

Actively involved in requirement discussions and refinements with client.

Analyzing customer requirements/problems and proposing quality solutions/architecture/POCs (AWS Stack), later developing on large scale (Petabytes).

Leading a team of 25 and managing the effective distribution of work among the team.

Maintaining data quality standards by standardizing unit tests, integration test and end to end test (Airflow) for every pipelines.

Designing and implementing the best practice of infrastructure as a code (Terraform).

Bringing new business to the company by getting involved in request for proposals (RFPs), pre-sales and solutioning.

Product and resource management, mentoring junior associates (helping them to develop competencies).

Data understanding and designed the architecture for the Vilua Datawarehouse. Also managed, scheduled, and designed the flow of ETL pipeline in Airflow.

Introduced and designed creative Vilua dashboard on open source dashboarding tool (Apache Superset).

Managed and designed CI/CD pipeline for the build, test, and deployment of ETL packages and User Interfaces.

Design and developing Data governance tool which makes data available for every person.

Designed architecture for privacy preserving federated learning.

Development for REST API for the deployment of Machine learning model in production.

Actively participated in teamwork to extend ML pipelines. Gathered requirements to perform OCR for new document support. Classification of documents into various categories. CI/CD of the product in agile manner (IDnow).

Engagement in requirement gathering phase to understand different data and sources. Developed, refined, and scaled data management pipelines. Accounted for designing of overall architecture to build Datawarehouse and maintained on-time delivery (BMW).

Migrated existing solution to containerized solution. Built new use cases for utilizing the in-house technologies and further extended the capability of containerized solution (use of NetApp persistent volume) (NetApp).

Close involvement in customer interactions for requirement gathering.

Managed risk and maintained quality of reporting solutions for many high-level projects.

Automated, developed, and integrated custom-built ETL adaptors with HPE and non-HPE products.

Effectively utilized Datawarehouse to build dashboard/visualization which helped customers to take necessary decisions for business.