Open to opportunities

Ali Bangash User

@alibangashuser

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Lead Data Engineer and Cloud Data Architect specializing in scalable data platforms.

United States

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What I'm looking for

I seek roles building scalable cloud-native data platforms, driving migrations, automating pipelines, and partnering with BI teams to enable analytics and data-driven decisions.

I am a results-driven Lead Data Engineer with 8+ years architecting scalable data solutions across cloud and on-premises environments, focused on real-time and batch data pipelines using Spark, Kafka, Airflow, Snowflake, and Databricks.

I have led cloud migration efforts (Hive/Hadoop to Snowflake on Azure), built Kafka-based IoT ingestion for near real-time analytics, and deployed cloud-native ETL frameworks leveraging ADF, S3, Redshift, and dbt to improve performance and reporting efficiency.

I am passionate about automation, data democratization, and enabling BI through solid data modeling and orchestration; I collaborate closely with BI and analytics teams to deliver production-ready pipelines and unified storage solutions.

Experience

Work history, roles, and key accomplishments

Current

Lead Data Engineer

Current

TDWI

Jan 2022 - Present (3 years 9 months)

Built scalable PySpark/Databricks and Airflow pipelines, migrated Hive/Hadoop workloads to Snowflake on Azure improving performance, and enabled near-real-time analytics via Kafka-based IoT ingestion.

Pyspark Databricks Apache Airflow Snowflake Kafka Azure Data Lake DBT

Data Engineer

Ignitec Inc

Jan 2018 - Jan 2022 (4 years)

Built and scheduled MapReduce, Hive, and Sqoop ETL jobs with Scala, modernized reporting with AWS Redshift and Airflow, and designed ingestion architecture handling 100M+ daily rows via Kafka and Spark Streaming.

Scala MapReduce Hive Sqoop Kafka AWS RedShift Apache Airflow

Data Analyst

Conceal

Jan 2016 - Jan 2018 (2 years)

Transitioned analytics to engineering by automating ETL and accelerating reporting, contributing as BI and data management consultant and supporting predictive analytics pipelines.