Shahida R. Khan, Developer in Dubai, United Arab Emirates
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Shahida R. Khan

Data Engineer and Developer

Dubai, United Arab Emirates

Toptal member since June 1, 2026

Bio

Shahida is a lead data infrastructure engineer with 12+ years of enterprise experience scaling cloud-native financial platforms and distributed lakehouses. She specializes in real-time streaming, transactional ledger reconciliation, and petabyte-scale ingestion. With a proven track record of establishing strict governance frameworks and driving deep FinOps optimizations that slash compute waste, Shahida excels at leading cross-functional engineering squads to deliver high-impact systems.

Portfolio

CDCX Technologies Pvt. Ltd
AWS IoT, Databricks, Apache Kafka, PySpark, Cassandra, MySQL, MongoDB, Python...
Margo Networks Pvt. Ltd.
Scala, Python, Spark, Hadoop, Apache Hive, Apache Kafka...
BigTree Entertainment Pvt. Ltd
Java, Scala, Spark, Hadoop, Apache Hive, Apache Kafka, Cloudera...

Experience

  • Hadoop - 10 years
  • MySQL - 10 years
  • Data Architecture - 8 years
  • Apache Kafka - 6 years
  • PySpark - 6 years
  • Databricks - 5 years
  • AWS IoT - 5 years
  • Python - 5 years

Preferred Environment

Apache Kafka, Elasticsearch, Databricks, AWS IoT, Data Architecture, PySpark, MySQL, Delta Lake, Data Engineering, Data Build Tool (dbt)

The most amazing...

...solution I've built is a real-time transactional financial ledger engine that scales to process millions of concurrent streaming events with zero data loss.

Work Experience

Lead and Staff Data Engineer

2022 - PRESENT
CDCX Technologies Pvt. Ltd
  • Architected and deployed an immutable real-time analytical ledger using AWS MSK and Spark Streaming, ensuring absolute pipeline idempotency for millions of concurrent financial transactions.
  • Engineered an optimized O(1) stateful lookup layer using Amazon DynamoDB as a cache, successfully reducing micro-batch end-to-end data processing latency from 24 hours down to under 60 seconds.
  • Spearheaded a platform-wide FinOps infrastructure audit across Databricks and AWS environments, implementing automated file compaction routines that slashed monthly compute waste by 30%.
  • Enforced automated schema validation guardrails using Unity Catalog and central Kafka Schema Registries, establishing an audit-ready data lineage compliant with strict financial regulations.
Technologies: AWS IoT, Databricks, Apache Kafka, PySpark, Cassandra, MySQL, MongoDB, Python, Spark, Data Architecture, Delta Lake, ETL, Amazon DynamoDB, Slack, Jira, Git, Software Engineering, Amazon MSK, DataOps, Financial Data, Data Pipelines, Data Lakes, Observability, Data Engineering, APIs, Amazon Web Services (AWS), REST APIs, Test-driven Development (TDD), Data Validation, Artificial Intelligence (AI), Data Science

Individual Contributor | Lead Data Engineer

2020 - 2022
Margo Networks Pvt. Ltd.
  • Conceptualized and built a decoupled storage and compute big data engine utilizing Apache Spark, Scala, and MongoDB to capture and index distributed edge-computing network tracking logs.
  • Established the division's core technical standards, institutionalized peer code reviews, standardized design templates, and mentored junior engineers on distributed systems.
  • Introduced automated DataOps CI/CD deployment guardrails and embedded runtime data validation checks using Great Expectations, reducing staging-to-production defect rates by 25%.
  • Optimized high-throughput distributed message processing layers using Apache Kafka clusters to guarantee zero-downtime ledger ingestion and real-time query availability.
  • Built prototypes and upheld best design and engineering practice, demonstrating the patterns.
Technologies: Scala, Python, Spark, Hadoop, Apache Hive, Apache Kafka, Hortonworks Data Platform (HDP), MongoDB, MySQL, Java, Google Cloud Platform (GCP), Data Architecture, ETL, PySpark, IntelliJ IDEA, Slack, Jira, Git, Software Engineering, DataOps, Data Pipelines, Data Lakes, Observability, Data Engineering, APIs, Kubernetes, Apache Airflow, Test-driven Development (TDD), Data Validation, Data Science

Data Engineer II

2017 - 2020
BigTree Entertainment Pvt. Ltd
  • Architected a decoupled, high-throughput Lambda data platform using Spark Streaming and Apache Kafka to ingest and process multiple petabytes of raw customer clickstream and social sentiment metrics.
  • Engineered distributed PySpark ETL pipelines on multi-node clusters, utilizing custom partitioning and broadcasting strategies to eliminate data skew and meet a strict 15-minute operational SLA.
  • Migrated legacy transactional data structures to a cloud-native Cloudera data lakehouse layout, delivering a 40% reduction in query execution times for downstream machine learning engines.
Technologies: Java, Scala, Spark, Hadoop, Apache Hive, Apache Kafka, Cloudera, Data Architecture, ETL, MySQL, IntelliJ IDEA, Slack, Jira, Git, Software Engineering, Data Pipelines, Data Lakes, Observability, Data Engineering, Kubernetes, Docker, Apache Airflow, Test-driven Development (TDD), Data Science

Data Analyst

2015 - 2016
Wipro Technologies
  • Developed multiple MapReduce jobs in Java for data cleaning and preprocessing, supporting those modules that are running on the cluster.
  • Configured and tuned core Hadoop ecosystem components, including HDFS storage layers, job tracker frameworks, and NameNode deployments, to maximize cluster resource utilization.
  • Programmed automated MapReduce workflows to cross-verify and reconcile large-scale historical datasets, reducing manual reporting data variance down to absolute zero.
Technologies: MapReduce, Java, Hadoop, HDFS, ETL, MySQL, IntelliJ IDEA, Slack, Jira, Git, Software Engineering, Data Engineering

Technical Support

2013 - 2015
Impact Infotech Pvt. Ltd
  • Acted as a single point of contact (SPOC) for all software installation requests, as well as their troubleshooting from various machines in India and London-based VDI machines dedicated to the finance and marketing domains.
  • Prepared the workload for rebuilding and allocating the Virtual Hard Disk (VHD) machine to business users as per their requirements.
  • Supervised the workload of the team, allocating team members to optimize service provision and administrative support across the hours of operation.
Technologies: IT Service Management (ITSM), Slack, Jira, Git

Experience

Real-time Transaction Ledger and Ingestion Platform

I designed and implemented an end-to-end cloud-native financial ledger engine that processes high-velocity trading data with zero data loss. I integrated AWS MSK (Kafka) stream ingestion with Apache Spark structured micro-batches. I also implemented atomic MERGE INTO operations on Delta Lake tables anchored on unique composite business hashes to guarantee deterministic recovery and pipeline idempotency. Finally, I substituted heavy network-wide shuffles with sub-millisecond DynamoDB lookups to seamlessly scale stream enrichment during intense market volatility.

DataOps Lifecycle Management and Cloud Optimization Program

I initiated a sweeping platform optimization track to remediate the Small File Problem across massive active data tiers. I programmed automated background file compaction and conditional VACUUM workflows on historical tables, cutting cloud compute waste on Databricks by 30% and saving $12,000 monthly. I also integrated Great Expectations into automated CI/CD pipelines to enforce mandatory runtime data quality assertions, reducing downstream staging-to-production data contract breaches to zero.

Petabyte-scale Behavioral Log Ingestion System

I architected a decoupled, high-throughput Lambda data platform to handle raw user clickstream and system performance tracking logs for millions of active daily users. I deployed distributed PySpark ETL pipelines on multi-node AWS EMR clusters. I also eliminated persistent data skew bottlenecks by implementing advanced, custom partitioning and broadcasting strategies, enabling the core analytical warehouse tables to meet a tight 15-minute data availability SLA for real-time recommendation engines.

Real-time Proof of Reserve (PoR) Pipeline & Digital Asset Inventory System

As a staff data engineer, I architected and single-handedly deployed a mission-critical proof of reserve (PoR) data pipeline from scratch to guarantee real-time cryptographic proof of funds for enterprise digital asset inventories. Operating as a strong individual contributor (IC), I owned the entire product lifecycle—from translating ambiguous financial requirements to executing the final production deployment.

I engineered a fault-tolerant ingestion framework that successfully aggregated high-velocity, fragmented data across Fireblocks vaults, centralized exchange APIs, and raw on-chain blockchain ledgers. To ensure 100% token coverage and zero-variance reporting, I built rigorous data reconciliation models with strict automated quality gates. I also authored comprehensive standard operating procedures (SOPs) to establish seamless operational governance for cross-functional teams.

This project demonstrated my ability to operate autonomously at a high level, maintaining absolute data reliability while executing at maximum speed. For architecting and deploying this fully production-ready pipeline in just two weeks, I was awarded the company-wide "Whale of the Quarter" honor for extraordinary performance.

2026 ISO Certification for an Enterprise Data Platform

As the lead data architect, I spearheaded the comprehensive security overhaul and governance restructuring of our enterprise data platform, successfully achieving ISO certification for 2026. Anticipating the strict regulatory and data sovereignty requirements of the MENA (Middle East and North Africa) region, I proactively designed and implemented robust security frameworks to ensure the platform was entirely audit-ready.

Operating as a highly autonomous IC and technical lead, I conducted rigorous pre-audit vulnerability assessments, identifying and resolving all critical security concerns prior to the external audit. I established strictly enforced data governance checklists, automated role-based access control (RBAC) validations, and comprehensive data encryption standards for data at rest and in transit.

By standardizing these compliance protocols and aligning our cloud infrastructure with MENA-specific enterprise security expectations, I ensured a flawless external audit with zero non-conformities. This project not only fortified the platform's security posture but also significantly elevated its commercial viability for enterprise and fintech clients operating in the Middle East.

Education

2010 - 2013

Bachelor's Degree in Information Technology

LN College of Commerce and Science - Mumbai, India

Skills

Libraries/APIs

PySpark, REST APIs

Tools

Slack, Jira, Git, Cloudera, IntelliJ IDEA, Apache Airflow, Apache Sqoop, Oozie, Apache NiFi

Languages

Python, Scala, Java

Frameworks

Spark, Hadoop

Paradigms

ETL, Test-driven Development (TDD), MapReduce, Role-based Access Control (RBAC)

Platforms

Apache Kafka, Databricks, AWS IoT, Amazon Web Services (AWS), Google Cloud Platform (GCP), Kubernetes, Docker, Hortonworks Data Platform (HDP), Blockchain

Storage

MySQL, Data Pipelines, Data Lakes, Data Validation, Apache Hive, HDFS, MongoDB, Elasticsearch, Amazon DynamoDB, HBase, Cassandra

Other

Software Engineering, Amazon MSK, Data Architecture, Delta Lake, Data Engineering, DataOps, Financial Data, Observability, IT Service Management (ITSM), APIs, Artificial Intelligence (AI), Data Science, Data Build Tool (dbt), API Integration (Fireblocks, Exchanges), End-to-end Deployment, ETL/ELT Pipelines, Distributed Systems, Data Governance, ISO Compliance, Auditing, Infrastructure Security, Cloud Security, Technical Leadership, Product Security, IT Security Audit and Assessment

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