Data Platform Architect & Engineering Leader

Farooq Tari

Lead Data Platform Engineer Cloud Data Architect Data Analyst

************@*****.*** 215-***-**** Pittsburgh, PA, 15120 Summary

Results-driven Data Engineering Leader with over 10 years of experience designing and implementing high- performance, scalable data infrastructure for Fortune 500 companies. Specializes in building cloud-agnostic data platforms, leveraging modern data stack technologies to enable advanced analytics and machine learning. Proven expertise in leading large-scale data migrations, optimizing data pipelines for cost and performance, and fostering a culture of data excellence. A collaborative leader passionate about mentoring high-performing teams to solve complex business challenges with robust, innovative data solutions. Skills

Data Platforms & Architecture

Data Lakehouse, Medallion Architecture, Data Mesh, Microservices, Event-Driven Architecture,

Dimensional Modeling (Kimball), Data Vault 2.0,

OLAP & OLTP Systems

Data Pipeline & Workflow Orchestration

Apache Airflow, Prefect, Dagster, dbt (data build

tool), Apache NiFi, AWS Step Functions, Azure Data Factory, Google Cloud Composer

Streaming & Real-Time Data

Apache Kafka, Google Cloud Pub/Sub, Apache

Pulsar, AWS Kinesis Data Streams, Spark Structured Streaming, Apache Flink

Machine Learning & Analytics

Feature Store Development, MLOps (MLflow,

Kubeflow), Scikit-learn, XGBoost, Jupyter

Notebooks, Statistical Analysis, A/B Testing

Frameworks

Data Architecture & Modeling

Data Mesh, Data Lakehouse (Databricks, Delta Lake), Data Vault 2.0, Kimball Dimensional Modeling,

Star/Snowflake Schemas, ERWin, ER/Studio

Cloud Platforms & Services

AWS (S3, Redshift, Glue, EMR, Lake Formation,

Lambda, IAM), Azure (Data Factory, Synapse,

Databricks, DevOps), GCP (BigQuery, Cloud

Composer, Dataflow, Pub/Sub)

BI & Visualization

Tableau, Power BI, Looker, Amazon QuickSight, SAP

BusinessObjects

Cloud Data Services & Warehousing

Snowflake, Databricks, Google BigQuery, Amazon

Redshift, Azure Synapse Analytics, AWS RDS, Azure

SQL Database, Cloud Spanner

Programming & Scripting

SQL (Advanced), Python (PySpark, SQLAlchemy,

Django), Java, Scala, JavaScript/Node.js, Bash/Shell Scripting

Monitoring & Data Quality

Great Expectations, Monte Carlo, Datafold, Grafana, Datadog, New Relic, Splunk, Prometheus

Data Governance & Security

Data Cataloging (Amundsen, DataHub), Column-

Level Encryption, RBAC, SOX Compliance, Data

Privacy (CCPA), Master Data Management (MDM)

Data Engineering & ETL/ELT

Apache Spark, dbt (data build tool), Apache Airflow, AWS Glue, Azure Data Factory, Informatica

PowerCenter, Talend, Stored Procedures

Databases & Storage

Snowflake, Amazon Redshift, Google BigQuery,

PostgreSQL, MySQL, SQL Server, Oracle, MongoDB,

DynamoDB

Professional Experience

Lead Data Engineer, Syncsort

•Designed and scaled batch and real-time data pipelines across AWS, Databricks, and Spark to integrate internal, external, and third-party datasets.

•Led the technical direction of data engineering teams, mentoring engineers on coding standards, testing practices, and architectural best practices. 03/ 2021 – Present

•Built and maintained lakehouse architectures (Delta Lake, Unity Catalog) with strong data modeling, lineage, and governance frameworks.

•Developed CI/CD pipelines with GitHub Actions, integrating automated testing, deployment, and infrastructure as code (Terraform/CloudFormation).

•Partnered with stakeholders to gather business requirements and deliver BI/analytics solutions using Tableau, MicroStrategy, and advanced SQL.

•Implemented serverless solutions (AWS Lambda, EMR Serverless, MSK, SNS, SQS) to optimize scalability and reduce operational costs.

•Enhanced data quality, fault tolerance, and monitoring, ensuring reliable mission- critical enterprise applications.

•Championed a customer-focused, One Team culture, aligning engineering initiatives with strategic business outcomes in both financial services and media. Senior Data Engineer, Quanterix

•Designed, developed, and maintained automated SOAR playbooks and workflows

(Google Chronicle, Cortex XSOAR, Splunk SOAR) to accelerate incident response, threat detection, and remediation, reducing MTTR significantly.

•Engineered scalable ETL pipelines from the ground up, enabling seamless processing of large, complex datasets across cloud environments (AWS, GCP, Azure).

04/ 2018 – 02/ 2021

•Built custom API integrations between SOAR platforms, SIEM, EDR, threat intelligence platforms, and case management systems (Jira, ServiceNow) to streamline security and data workflows.

•Developed Python-based automation scripts for security orchestration, data enrichment, and ETL transformations, ensuring clean, efficient, and reusable code.

•Partnered with SOC teams, threat intelligence groups, and product managers to translate operational needs into technical requirements for data pipelines and security automation.

•Mentored junior engineers and analysts, establishing best practices for automation development, data modeling, testing, and CI/CD workflows.

•Enhanced operational efficiency by identifying and automating manual security and data tasks, improving system reliability, scalability, and performance.

•Documented integrations, playbooks, and workflows while ensuring compliance with cybersecurity standards and data governance practices. Data Analyst, Zulily

•Led the design, development, and support of enterprise-wide BI applications and architectures, with hands-on expertise in Databricks, Power BI, and database diagramming.

•Partnered with senior business and IT stakeholders to define, source, and prioritize data requirements, ensuring alignment with strategic objectives. 02/ 2016 – 01/ 2018

•Designed and implemented data models, mappings, and ETL processes (SQL, Alteryx) to integrate, cleanse, and transform large-scale datasets across multiple platforms.

•Optimized BI tools and dashboards by defining performance filters, indexes, and conducting extensive data quality checks and validation.

•Collaborated with cross-functional and offshore teams, acting as SME to clarify functional and business questions, while supporting project tracking through Agile/SDLC lifecycles.

•Worked with cybersecurity and product datasets, ensuring secure ingestion, normalization, and analysis while applying data security best practices.

•Developed and delivered training to empower business users, enhancing decision-making through self-service BI capabilities.

•Authored technical and business documentation, including data interface specifications, business/technical requirements, and testing methodologies. Projects

Unified Customer Data Platform

Architected a central customer 360-degree platform on AWS, integrating data from web, mobile, and CRM systems using Kafka and Glue. The platform powered a real-time recommendation engine, resulting in a 15 percent increase in customer engagement.

Predictive Maintenance for IoT Fleet

Engineered a solution to process telemetry data from 50,000 industrial sensors using Azure IoT Hub and Stream Analytics. Developed a predictive model in Azure ML to forecast equipment failures, reducing downtime by 25 percent and saving $2M annually in maintenance costs. Modern Data Stack Migration

Led the successful migration from an on-premise Hadoop cluster to a modern cloud stack (Snowflake, dbt, Airflow, Tableau).

Certificates

•AWS Certified Solutions

Architect – Professional

•Databricks Certified Associate

Developer for Apache Spark

•Google Cloud Professional

Data Engineer

Education

Bachelor of Computer Science 2015

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