Open to opportunities

Huzz Sindhu

@huzzsindhu

Staff Data Engineer specializing in multi-cloud lakehouses, real-time streaming, and AI-ready data platforms that cut costs and speed insights.

United States

Message

What I'm looking for

I’m looking to build and own end-to-end data platform strategy—multi-cloud lakehouses, real-time streaming, and AI-ready layers—while driving reliability, governance, and cost efficiency. I thrive partnering with data science and analytics teams in fast-moving environments.

I’m a Staff Data Engineer with 11 years designing and scaling enterprise data platforms across fintech, healthcare, SaaS, supply chain, and retail. I own end-to-end platform strategy—architecture and data governance through to team mentorship and stakeholder alignment—while staying comfortable driving technical decisions solo or leading cross-functional engineering in fast-moving environments.

I build lakehouse and streaming systems that deliver measurable impact: multi-cloud medallion architectures for real-time financial analytics, CDC + Kafka + Spark Structured Streaming pipelines with sub-second latency, and dbt semantic/metric layers that unlock self-service analytics at scale. I also enforce compliance and reliability with Unity Catalog RBAC, PII masking, lineage/observability, automated quality checks (e.g., Great Expectations), and SLA monitoring—cutting cloud costs by 30%, reducing mean time to detect by 60%, and accelerating ML training cycle time by 40% through AI-ready feature engineering and RAG-ready data layers.

Experience

Work history, roles, and key accomplishments

Current

Staff Data Engineer

Current

Lateetud

Sep 2023 - Present (2 years 7 months)

Architected a multi-cloud lakehouse on AWS and Azure for real-time financial analytics, delivering CDC + Kafka + Spark Structured Streaming with sub-second latency. Reduced cloud costs 30%, improved pipeline MTTR by 60%, and enforced SOC 2 and GDPR compliance using Unity Catalog RBAC, PII masking, and automated data quality checks.

Lakehouse Snowflake Databricks Kafka Spark Structured Streaming DBT Unity Catalog SOC II GDPR Terraform

Senior Data Engineer

Analytics8

Jul 2021 - Aug 2023 (2 years 1 month)

Designed a HIPAA-compliant lakehouse on Azure using ADLS Gen2, Databricks, and Snowflake, building batch/incremental/CDC pipelines into a medallion architecture. Implemented SCD Type 2 modeling and automated data quality frameworks, and delivered dbt semantic/metric layers for Power BI while reducing ML training cycle time by 40%.

Azure ADLS Gen2 Databricks Snowflake DBT Power BI Data Quality CI CD

Data Engineer

Creole Studios

Jun 2018 - Jun 2021 (3 years)

Built cloud-native data pipelines on AWS using S3, Redshift, and Airflow to ingest application events, clickstream, and SaaS data at scale. Developed near real-time Kafka + Spark Structured Streaming for live product analytics, implemented dbt analytics engineering, and supported churn/LTV feature pipelines while reducing SLA breaches through more reliable ETL workflows.

AWS S3 Amazon Redshift Apache Airflow Kafka Spark Structured Streaming DBT A B Testing Salesforce Stripe Segment

Associate Data Engineer

BigChalk

Aug 2015 - May 2018 (2 years 9 months)

Built ETL pipelines ingesting ERP, POS, and logistics data into a centralized warehouse for supply chain and retail analytics. Designed dimensional star-schema models, contributed to cloud migration, and implemented automated validation/reconciliation to reduce manual correction effort and improve operational reporting.