Nazish Mehdi

As a Senior Solutions Analyst, I am driven by a deep ambition for mastery, meticulously applying logic and diligence to every challenge. My pragmatic and structured approach ensures the development of compliant and highly effective solutions. I am dedicated to continuous improvement and delivering optimal outcomes.

Open to

Bangalore · Dubai · Hyderabad

Work style

Onsite, Hybrid

Availability

Available in 30 days

Degree confirmed by Maharaja Institute of Technology Mysore, Pentagon Space

Contact details — on requestProof of Work — on request

Experience

Senior Solutions Analyst

ThoughtSpot · Aug 2024 – Present

Not yet confirmed

Designed, built, and maintained ETL/ELT pipelines for 50+ enterprise customers integrating data from multiple sources and vendors (APIs, cloud storage, relational databases, CRM/ERP systems) into governed Snowflake data warehouse environments.
Built and managed data warehouse solutions end-to-end designing dimensional data models (fact/dimension tables, star/snowflake schema, SCD handling), creating ETL processes, and implementing data quality mechanisms to ensure reliable analytical data.
Performed exploratory data analysis (EDA) to troubleshoot data-related issues identifying root causes of data quality problems, analysing pipeline failures, and implementing permanent fixes to ensure data integrity across production systems.
Managed direct client interactions engaging with technical and business stakeholders to understand data requirements, present engineering solutions, and provide ongoing technical guidance throughout delivery engagements.
Provided mentoring and technical guidance to junior analysts - reviewing data models and pipeline designs, supporting skill development, and ensuring consistent engineering standards across the team.
Integrated data from multiple enterprise sources including CRM (Salesforce-adjacent), operational databases, flat files, APIs, and cloud storage into unified Snowflake data platforms supporting holistic analytical insights.
Implemented end-to-end data quality and data governance mechanisms
validation rules, completeness checks, data lineage documentation, audit trails, and access controls (RLS, PII masking) across production data pipelines.
Optimised Databricks and Snowflake workloads applying PySpark optimisation techniques, virtual warehouse tuning, clustering keys, and materialised views to improve pipeline performance and reduce compute costs.
Managed Apache Airflow/Cloud Composer DAG orchestration designing dependency chains, retry logic, SLA-driven scheduling, and alerting for production ETL workflows.
Worked with AWS services (EC2, S3) and Azure for cloud data engineering
integrating cloud storage, managing data ingestion workflows, and ensuring multi-cloud data platform reliability.
Maintained Git-based CI/CD workflows - version-controlled deployments, code reviews, and release governance for all ETL pipeline and data model assets.

Data Analyst

SagasIT Analytics / AIMLEAP · Mar 2021 – Apr 2023

Not yet confirmed

ETL Pipeline Development: Built Python-based ETL pipelines REST API extraction, Pandas/PySpark-equivalent transformation, and BigQuery loading with quality validation, scheduling, and error handling.
Data Warehouse Engineering: Designed PostgreSQL schemas with stored procedures, fact/dimension-style table structures, complex SQL queries, and data integrity controls for analytical workloads.
EDA & Data Issue Resolution: Performed exploratory data analysis to identify data quality issues, inconsistencies, and pipeline anomalies resolving root causes and implementing preventive data quality checks.
Cloud Infrastructure: Built data pipelines on AWS EC2 with S3 storage - managing structured and semi-structured data ingestion, transformation, and loading at scale.
Automation: Automated data workflows using Python and UiPath reducing manual toil and improving ETL pipeline reliability and operational efficiency.

Skills 0 proven through work

Also works with

Foreign Key ImplementationCheck Constraint ImplementationDimension Table DesignFact Table DesignOLTP Design PrinciplesOLAP Design PrinciplesAnalytical Workload DesignOpenMetadata UsagePandera UsageSQLAlchemy UsageData EngineeringTeamworkTechnical Training DeliveryMentoring and Peer CoachingEmployee Onboarding CoordinationCron Job SchedulingMaterialized View DevelopmentSlowly Changing Dimensions ImplementationData MaintenanceDatabase Query OptimizationTable Partitioning ImplementationDatabase NormalizationStored Procedure DevelopmentData Architecture DesignError HandlingPII RedactionPolars Dataframe Usagepandas UsageAPI Caching ImplementationPydantic UsageHive UsageData LoadingData TransformationData ExtractionAPI IntegrationCode ReviewImpact AnalysisAudit Log ImplementationApache Airflow OrchestrationData DocumentationDatabase TestingData MonitoringData ValidationData GovernanceData Integrity ManagementStar Schema DesignData Mart DevelopmentBusiness Logic ImplementationData CurationAmazon S3Query WritingAWS Athena UsageBatch Processing ImplementationAWS EMR UsageTask SchedulingAWS GlueData CatalogingData Partitioning and Segregation DesignMedallion Architecture DesignData ModelingDBT UsageLooker UsageTableauPower BIAmazon Redshift UsagePostgreSQL Database UsagePython DevelopmentAWS DeploymentDatabricks UsageETL Pipeline Development

Proof of Work

Nazish shares this with people who ask. You'll hear back either way.

Education

B.E., Electronics and Communications

Maharaja Institute of Technology Mysore · 2016 — 2020

Maharaja Institute of Technology MysoreVerified

Course, Artificial Intelligence and Machine Learning

Pentagon Space · 2020 — 2020

Pentagon SpaceVerified

Links

linkedin.com/in/nazishmehdi-80b0a5188

Contact details

Nazish shares this with people who ask. You'll hear back either way.

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