Open to opportunities

Ali Bangash

@alibangash4

Message

Data Solutions Architect building cloud-native lakehouse and ETL/streaming pipelines with AI-driven analytics.

United States

Message

What I'm looking for

I’m looking to design and scale cloud-native data lakehouse platforms—owning ETL/streaming, governance, and AI/LLM (RAG) workflows—so teams can turn complex data into real-time business decisions with measurable reliability and performance.

I’m a Data Solutions Architect with 11+ years of experience designing and building scalable, AI-driven data platforms and ETL/ELT pipelines. I translate business needs into architectures that enable efficient ingestion, transformation, and analytics—built for both batch and real-time use cases.

My work focuses on cloud-native lakehouse architectures and enterprise-grade data platforms using AWS, Azure, Databricks, Snowflake, and BigQuery. I integrate LLM workflows—including retrieval-augmented generation (RAG), LangChain, and LlamaIndex—to deliver intelligent analytics and data access.

I’ve led end-to-end solution delivery across healthcare, financial services, and retail, including Kafka/Spark Streaming-based processing for high-volume systems. I also establish data governance, security, and compliance foundations such as data lineage, access control, and metadata management to keep platforms trustworthy.

Throughout my career, I’ve mentored engineers and aligned AI and data strategies with organizational goals. Whether modeling dimensional warehouses (Kimball/Star) or implementing Data Vault approaches, I aim to improve system performance, scalability, and reliability—so teams can act on insights faster.

Experience

Work history, roles, and key accomplishments

Current

Data Solutions Architect

Current

ScienceSoft

Feb 2024 - Present (2 years 2 months)

Designed end-to-end data solutions on AWS and Azure, translating business needs into scalable lakehouse architectures for healthcare and financial analytics. Built batch and real-time pipelines using Databricks, Snowflake, Kafka, and Spark Streaming, and integrated LLM-based querying with governance and compliance controls.

AWS Azure Databricks Snowflake Lakehouse Apache Kafka MLFlow Data Governance Retrieval Augmented Generation (RAG)

Lead Data Engineer

NexHealth

Apr 2021 - Jan 2024 (2 years 9 months)

Engineered scalable healthcare pipelines for EHR and claims data, enabling near real-time analytics for clinical reporting and population health. Orchestrated HL7/FHIR ingestion and delivered HIPAA-compliant lakehouse and warehousing solutions, automating ETL monitoring/testing and reducing pipeline failures by 35%.

Apache Spark Python Apache Airflow Apache NiFi HL7 FHIR Databricks Snowflake

Senior Data Engineer

SentiLink

Developed large-scale batch and streaming pipelines with Spark, Kafka, and Hadoop to process millions of transactions for fraud detection and risk analysis. Built data storage and warehousing solutions and collaborated with data science to deploy ML models using Python, scikit-learn, and MLflow.

Apache Spark Apache Kafka Hadoop Hive Amazon S3 Amazon Redshift Snowflake MLFlow

ETL & Data Warehouse Engineer

FourKites

Developed and maintained enterprise ETL pipelines to integrate retail and POS datasets into centralized warehouse systems using Informatica, Talend, and SSIS. Migrated on-prem data to AWS and BigQuery, built near real-time ingestion with NiFi, optimized SQL/Spark performance, and delivered BI dashboards for supply chain and sales decision-making.

Informatica Talend SSIS Apache NiFi AWS BigQuery Apache Spark Power BI