Description

I am a results-driven Senior Data Engineer with over a decade of IT experience, specializing in architecting scalable Data Lakehouse solutions across AWS and GCP. I bridge the gap between complex raw data and actionable business intelligence, helping organizations like HelloFresh and Accenture transform their data infrastructure into a competitive advantage.

What I Bring to Your Project

• Modern ELT Orchestration: Extensive experience building robust pipelines using dbt, Apache Airflow, and Dagster to automate data delivery and reduce manual intervention by up to 40%.

• High-Performance Architecture: Proven track record of optimizing data models (Kimball/Star Schema) that reduce processing times by 30% and significantly improve query performance for BI tools like Tableau and Looker.

• Cloud Data Warehousing: Deep technical expertise in Snowflake, Databricks, and Google BigQuery, ensuring your data is stored efficiently and scales seamlessly.

• AI & Real-Time Analytics: I don't just move data; I make it "smart." I recently developed a Real-Time Analytics Bot using Anthropic Claude 3.5 and implemented Kafka streaming for event-based ingestion.

• Data Quality & Governance: I implement rigorous testing and documentation frameworks within dbt to maintain 98%+ data accuracy and ensure GDPR-compliant data integrity.

Technical Toolkit

• Languages: SQL (Expert), Python (Pandas/PySpark), Shell Scripting.

• Cloud: AWS (S3, EC2, Lambda), GCP (Data Composer, BigQuery), Databricks.

• Transformation/Ops: dbt, Airflow, Docker, Kubernetes, CI/CD (Jenkins/GitHub Actions).

Why Hire Me?

Based in Canada but highly experienced in collaborating with global teams, I offer a unique blend of senior leadership and hands-on technical execution. Whether you need to build a greenfield data platform or optimize a legacy pipeline, I deliver world-class solutions that empower your analysts and executives.

Languages

English
Native or bilingual

Workplace preferences

Can work on-site

Toronto (up to 50km)

Hello Fresh Canada
Senior Data Engineer
DIGITAL AND IT
January 2025 - Today (1 year and 7 months)
Hybrid, Tbilisi, Georgia
• •
• • Developed and deployed robust ELT pipelines using DBT and Airflow, integrating diverse and high-volume data into Snowflake, Databricks, and BigQuery.
• • Designed data models using Kimball methodology (star schema with fact and dimension tables) in DBT, improving query performance and enabling consistent analytics across business domains.
• • Architected and optimized DBT models with efficient query design and incremental logic, reducing data processing time by over 30%.
• • Utilized DBT's testing and documentation features to maintain data quality and integrity of fact/dimension tables across Snowflake and BigQuery.
• • Built and optimized DBT models, reducing data processing time by 30% through efficient query design and leveraging incremental logic.
• • Utilized DBT's testing and documentation capabilities to maintain data quality, catching issues early and preventing errors in production datasets.
• • Collaborated with data analysts and data scientists to ensure alignment between raw data and the end-user requirements, resulting in more efficient data usage.
• • Orchestrated workflows using DBT and Airflow, automating data pipeline execution and monitoring, reducing manual intervention by 40%.
• • Implemented data versioning and auditing, ensuring reproducible and consistent data transformations in the analytics layer.
• • Ensured data integrity, consistency, and quality across all data layers, leveraging DBT testing and quality frameworks.
• • Worked closely with global marketing teams to develop business-essential, impactful analytical pipelines using DBT, Snowflake, and PySpark.
• • Developed a data analytics bot using Anthropic Claude 3.5 for real-time analytics for executives.
• • Created a self-service analytics pipeline and dashboards for HelloFresh's marketing teams using ad data from Facebook, TikTok, Horizon, and Google.
• •
BigQuery Python DBT Data integration (ETL, ELT and data warehousing) SQL
Quartech
Data Engineer
January 2024 - January 2025 (1 year)
Remote Remote, Mahesana, GJ, India
• • Designed and implemented end-to-end ELT pipelines using DBT, Apache Airflow, and Databricks, integrating high-volume data from various sources into Snowflake and databricks.
• • Built and optimized over 50+ DBT models, reducing data processing times by 30% through efficient query design.
• • Orchestrated workflows using Airflow, reducing manual intervention by 40%.
• • Implemented data versioning and auditing, ensuring reproducible and consistent transformations.
Databricks DBT Snowflake AWS Glue
FPT Canada
Data Engineer
November 2022 - January 2024 (1 year and 2 months)
Toronto, ON, Canada
• • Led the design and implementation of DBT data models and pipelines for business intelligence and data science use cases.
• • Wrote SQL-based transformation logic in DBT to standardize and integrate disparate data sources into a unified data model.
• • Improved DBT model performance by restructuring data transformations, leading to a 25% improvement in data load times. Assisted in building and optimizing data pipelines using
DBT, Big query and Apache Airflow on GCP ( Data Composer), allowing for efficient data processing across different stages.
• •
• • Created reusable macros and models in DBT to allow for easy scaling of new data transformation workflows, minimizing repetitive tasks for the team.
• • Actively participated in code reviews to ensure data modeling standards and consistency across the team.
• • Worked closely with stakeholders to define data transformation requirements and optimize existing DBT models based on feedback
SQL Business Intelligence (BI) Strategy DBT Airflow Dataflow