Nimish Choudhary

Data and AI Leadership Expert (18 Years):

Seasoned professional and consultant specializing in the development of data strategies and data platform modernizations, boasting an impressive 18-year track record.

Assisting organizations in the monetization of data and the design of data products through the use of visualization and AI/ML to generate valuable insights.

Head of the Data Architect Community with over 100 members, responsible for managing organizational structure, fostering career growth, driving client engagement, and setting strategies for Big Data and AI projects. Leads innovation in the realm of data.

Sales Technology Consultant and Client Engagement Specialist:

Adept sales technology advisor collaborating with sales and pre-sales teams, contributing to proposals, analyzing client needs, and proposing effective data architecture solutions. Proficient in engaging with clients, including CxO level teams.

Regional SPOC for Data Engineering (Globant-UK):

Serving as the Single Point of Contact (SPOC) for Data Engineering in the UK region at Globant, liaising between client partners, senior leadership, and various technology leaders (SAP, Salesforce, Oracle, Mulesoft, UI/UX, Mobile) to drive end-to-end digital transformation.

Data-driven Excellence and Strategic Leadership:

Lead comprehensive data strategy, emphasizing cost-effectiveness and alignment with strategic goals. Drive senior-level initiatives for data management, fostering a data-centric culture. Enforce data governance policies, ensuring quality, security, and compliance. Oversee controls for data quality, monitoring metrics, and maintaining accurate, consistent, and accessible data. Supervise data architecture design, optimization, and adoption of cutting-edge technologies.

Worked across multiple industries such as financial services, insurance, telecommunications, healthcare, retail, and travel/tourism.

• AI x 4 | Google x 14 | AWS X 1 | Teradata X 2 | IBM X 8 | LinkedIn X 1
• https://www.linkedin.com/in/nimish-choudhary-59a21b14/details/certifications/

Company: Globant, India

Role: Data Strategist
(Mar, 23 – Till date)

Project: Integrating multiple applications to build a central data hub for a government-funded e-commerce startup in Saudi Arabia, focusing on women's wellbeing.

Technology stack: AWS, Mulesoft, OIC

Responsibility:

• Analyze application integration use cases and create data mappings for the applications.
• Define data products and devise a data platform strategy.
• Develop proposals for innovative products such as Chatbots and Health Device data analytics.
• Create a high-level implementation plan, estimate effort, establish timelines, and define deliverables.

Role: Subject Matter Expert and Technical Leader
(July, 22 – Dec, 22)

Project: Migrate legacy systems (batch and stream) to AWS cloud using framework-driven ETL pipelines and enable DataMesh analytics across multiple domains.

Technology stack: AWS, Kafka, Glue, Lambda, Lake formation, S3, Athena, Airflow

Responsibility:

• Analyze On-Premise platform, including SQL server, APIs, Clickstream, and PowerBI.
• Develop conceptual, logical, and physical data model.
• Design solution with lambda architecture using Kafka, S3, Glue, Lambda.
• Create epics and stories with acceptance criteria and estimations.
• Identify milestones and plan resources.
• Interact with CxO, Head of, and Director to inform them of the current plan, strategy, and status.
• Manage a team of 30 Data Engineers and two Architects.
• Participate actively in daily status calls, sprint planning, story grooming, etc.

Role: Cloud Data Architect
(February, 21 – June, 22)

Project: Building data platform to apply analytics on the logging of Robotic Process Automation platform - BluePrism and UiPath.

Technology stack: Splunk, SSIS, SQL server, PowerBI, Databricks, Azure Data Factory

Responsibility:

• Analyze On-Premise platform, including RPA logs, SSIS, Splunk, and PowerBI.
• Identify challenges, limitations, and future opportunities.
• Design cloud-based solutions using Azure's technology stack.
• Improve existing platforms through ETL/SSIS and SQL optimization.
• Assist PowerBI users and engineers in preparing effective data models.
• Mentor data scientists in the use of platform resources.

Role: Cloud Data Architect
(August, 20 – January, 21)

Project: Creating a unified Hive data model from heterogeneous source applications to generate enterprise-level reporting for CxOs.

Technology stack: Hadoop, Hive, Spark, NiFi, Apache Ranger, Apache Atlas

Responsibility:

• Analyze heterogeneous sources to prepare a unified Hive data model.
• Review and apply best practices for Hadoop in Hive and Spark.
• Assimilate source application data into the standard data model.
• Document data processing, including data flow, transformation, and quality checks.
• Work closely with data engineers to explain functional requirements and validate results.

Company: Globant, India
(Jan, 20 – Sept, 20)

Problem: The client, a leading financial services company in the US, faced performance issues with Azure SQL and SSIS due to growing data. They needed a future-proof solution within Azure Stack.

Technology stack: SSIS, SQL Server, Azure Data Factory, Azure Synapse analytics, Delta Lake, Databricks

Activities:

• Interact with customer and sales team to define the problem.
• Identify source application, data variety, ingestion, processing, architecture, design, model, consumption, growth, security, compliance, CI/CD pipeline, server details, etc.
• Obtain input from client's SMEs.
• Propose As-Is and To-Be architecture, capacity planning, team planning, effort estimation, and compare with alternatives.
• Discuss solution with stakeholders and conclude with negotiation.
• Implement end-to-end solution using Azure SQL, SSIS, ADF, and Azure Synapse.

Achievements:

• Reduced Time To Market for existing reports by 30%-50%.
• Reduced ETL components by 20%.
• Improved ETL execution time by 40%-50%.
• Implemented a generic data model, reducing database objects by 60%.
• Enabled processing of unstructured and streaming data using Spark.
• Expanded AI and ML capabilities.

Company: Globant, India
(Nov, 19 – Dec, 19)

Problem: The client, a leading pharma company in the US, required an automated solution to record the voice of a Medical Representative and store it in text format in a Relational database with minimal maintenance.

Activities:

• Interact with client and sales team to define the problem.
• Formulate questionnaire for data consumption case.
• Interact with client's SME to understand desired conversation recording.
• Plan To-Be solution architecture, capacity planning, team planning, effort estimation.
• Develop POC using Google Assistant, DialogFlow, and MySQL.
• Present demo and proposal to stakeholders, conclude with negotiation.

Achievements:

• Implemented mobile and web applications for recording conversations.
• Trained Dialog Flow with medical terminology for accuracy.
• Implemented advanced analytics on stored information, including sentiment analysis.

Company: Datametica, India
(Jan, 18 – June, 19)

Role: Technical Architect
Project: Data-warehouse offloads from MS SQL server to AWS.

Responsibility:

• Ensure long-term client relationships, network, and cultivate business development opportunities.
• Design hybrid data lakes with on-premise sources and cloud sinks.
• Gather requirements, define scope, estimate, build a team, and plan sprints.
• Setup batch framework for data ingestion with auditing, scheduling, and failure handling.
• Handle one-time load of 40 TB and incremental loads of 1 GB per batch.
• Implement transformation layer with automated lookups.
• Refresh Athena database for reporting users.
• Extract incremental data from MS SQL server every 5 minutes to S3 using Kinesis and Redis in near real-time.

Achievements:

• Reduced storage costs by almost 40%.
• Reduced analytical query execution time by 20%-30%.

Company: Datametica, India
(Mar, 17 – May, 17)

Role: Technical Architect
Project: EDW reporting layer offload from Teradata/Informatica to GCP.

Responsibility:

• Direct daily progress of engagement work, inform engagement manager, manage staff performance.
• Use hybrid data lakes for on-premise sources and cloud sinks.
• Determine scope, document existing EDW logic and transformation.
• Handle one-time historical data load of 50 TB and incremental data load of 2 GB/day.
• Load reporting data into BigQuery for ad-hoc analysis and scheduled reports.
• Implement SCD-2 and necessary transformations.
• Automate data ingest and validation.

Achievements:

• 40% reduction in infrastructure and licensing costs.
• Enabled personalized recommendations to customers through advanced analytics.

Company: Datametica, India
(Jan, 17 – June, 19)

Role: Technical Pre-Sales Architect
Responsibility:

• Meet with client (technical team, DBA, etc.) to assess existing data warehouse.
• Present summary and solution architecture at CXO level.
• Define and document architecture, capture requirements, prepare estimates, and propose technical solutions.
• Prepare reports based on EDW metadata processing.
• Review data flow and access patterns for reporting priorities.
• Develop EDW offload approach using Hadoop.
• Connect with product team, pre-sales team, and technical architect for relevant information.
• Provide feedback for new features and improvements.
• Implement pilot project to migrate from traditional EDW to modern big data lake using sqoop, hive, spark, big query, etc.

Snapshot of Data Warehouse experience:

Wipro | ETL Architect | Mar, 15 – Dec, 17 | Teradata, Informatica

Hexaware | ETL Lead | May, 11 - May, 15 | Teradata, Informatica, Oracle

TCS | ETL Lead | Jul, 10 - Apr,11 | Teradata, Informatica

Infosys | ETL Developer | Sep, 06 - Jul, 10 | Oracle, Teradata