Senior Data Engineer & Cloud Data Architect

Hassaan Arsh

Senior/Principal Data Engineer Cloud Data Architect

***********.**@*****.*** +1-226-***-**** Lucan, ON NOM 2J0

Professional Summary

Highly experienced Data Engineer with 10 years of proven expertise in designing, developing, and operating

scalable, cloud-native data platforms across analytics, product, and operational systems. Skilled in end-to-end

data architecture, including ETL/ELT pipelines, lakehouse & data warehouse design, streaming & event-driven

architectures, cloud platforms, and governance frameworks.

Proven track record of leading data platform initiatives from design through production, improving data

quality, reliability, and performance while enabling self-service analytics and ML pipelines. Recognized for

technical leadership, mentoring engineers, and translating business needs into robust, secure, and highly

available data solutions. Adept at startups, scale-ups, and enterprise environments, making data platforms

enterprise-ready, cost-efficient, and future-proof.

Skills

Data Engineering & Architecture Data Quality, Governance & Observability

End-to-End ETL/ ELT Pipeline Design (Batch & Data Reliability Engineering (DRE), SLAs & SLOs

Streaming) Data Warehousing & Lakehouse Data Validation, Lineage & Traceability Data

Architecture Dimensional & Analytical Data Governance & Security (GDPR, SOC2, IAM, RBAC)

Modeling (Star, Snowflake, 3NF) Event-Driven & Observability: Prometheus, Grafana, Alerts &

Near Real-Time Data Systems Change Data Capture Dashboards

(CDC) & Data Ingestion Scalable, Fault-Tolerant,

Multi-Region Systems Orchestration & DevOps

Apache Airflow, Dagster, Prefect (Advanced DAGs)

Cloud & Data Platforms CI/ CD Pipelines & GitHub Actions Containerization

AWS (S3, Redshift, Glue, Athena, Lambda, EMR) GCP & Infrastructure as Code (Docker, Terraform)

(BigQuery, Dataflow, Pub/ Sub) Azure (Data Factory, Monitoring, Logging, Backfills, and Failure Recovery

Synapse, Blob Storage) Cloud-Native Architectures,

Cost Optimization, Auto-Scaling Programming & Query Optimization

Python, SQL (Advanced, Optimization, Stored

Streaming & Real-Time Processing Procedures) Spark, Scala, Java Performance

Apache Kafka, Kafka Connect, Spark Structured Tuning for Large-Scale Analytical Workloads

Streaming AWS Kinesis, GCP Pub/ Sub Event

Stream Processing, Windowing, Transformation Analytics & BI Enablement

Analytics-Ready Datasets, Data Marts, Semantic &

Databases & Storage Metrics Layers Integration with BI Tools (Looker,

PostgreSQL, MySQL, MongoDB, DynamoDB, Tableau, PowerBI) Support for Data Science & ML

Cassandra Snowflake, Databricks Pipelines

Leadership & Collaboration Machine Learning Data Pipelines

Technical Ownership & Platform Roadmaps Feature engineering, training & inference datasets,

Mentorship & Team Leadership Cross-Functional and ML-ready data platform support.

Stakeholder Communication Agile, Scrum, and

Sprint-Based Development

Data Observability & Monitoring

Automated monitoring, anomaly detection, lineage

tracking, and proactive alerting for reliable

pipelines.

Professional Experience

Senior/Principal Data Engineer, Adastra Corporation 01/2022 – Present

• Lead design and development of a modern cloud data platform, leveraging AWS

S3, Redshift, Lambda, and Snowflake to support analytics, reporting, and ML

workloads.

• Built high-throughput ETL/ ELT pipelines processing multi-terabyte daily datasets,

improving freshness, availability, and reliability by 40%+

• Architected real-time streaming pipelines using Kafka and Spark Structured

Streaming, enabling near real-time dashboards and alerts.

• Implemented data quality and observability frameworks, reducing production

data incidents by 45% and maintaining SLA compliance.

• Optimized warehouse and lakehouse performance, achieving ~30% annual

infrastructure cost reduction through partitioning, clustering, and query tuning.

• Mentored 4+ mid and senior data engineers, conducted architecture reviews, and

led platform roadmap planning.

• Collaborated with product, analytics, and ML teams to deliver feature-ready

datasets, supporting AI/ ML initiatives.

• Designed and enforced data governance, lineage, and compliance standards,

ensuring secure, auditable, and trusted data across the organization.

• Led initiatives to standardize analytics-ready datasets and semantic layers,

improving BI adoption and reducing inconsistencies across reporting tools.

Senior Data Engineer, Ataccama Corporation 06/2017 – 12/2021

• Developed and maintained batch ETL pipelines ingesting structured and semi-

structured data from multiple sources.

• Designed and optimized cloud data warehouses and analytics-ready data models

for finance, operations, and product teams.

• Implemented data validation, quality checks, and monitoring, improving trust

and reducing downtime.

• Collaborated with stakeholders to create self-service BI datasets, dashboards, and

operational reports.

• Refactored SQL queries and optimized ETL workflows, reducing pipeline run

times by 25%+

Junior Data Engineer, TechnoData Analytics Services 07/2014 – 05/2017

• Developed batch ETL pipelines for business and operational data ingestion.

• Assisted in building dimensional models and data marts to support analytics and

reporting.

• Wrote Python scripts and SQL queries to transform and clean large datasets.

• Partnered with analytics and product teams to deliver actionable datasets.

• Maintained documentation and knowledge bases for data pipelines and models.

KEY PROJECTS

Modern Cloud Data Platform

• Designed centralized data lakehouse and warehouse on AWS/ Snowflake.

• Integrated batch and streaming pipelines, supporting real-time dashboards, ML features, and analytics-

ready datasets.

• Reduced data delivery times by 40% and improved governance & lineage.

Data Warehouse Optimization & Migration

• Refactored legacy warehouses and pipelines during migration to modern cloud stack.

• Optimized queries, reduced compute costs, and enabled near real-time reporting.

• Improved platform reliability and maintainability, enabling enterprise-grade analytics.

Certificates

Databricks Lakehouse AWS Certified Data Analytics - Google Professional Data

Fundamentals Specialty Engineer

Lakehouse architecture, Delta Advanced cloud data analytics Designing, building,

Lake, and Spark-based data and ETL/ ELT expertise on AWS. operationalizing, and securing

pipelines. data processing systems on GCP.

Microsoft Azure Data Engineer

Associate (DP-203)

Implementing cloud data

solutions, pipelines, and

governance on Azure.

Education

Bachelor of Science in Computer Science (BSCS)

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