Senior Data & Analytics Architect for Cloud Platforms

Hadi Altaf

SENIOR DATA & ANALYTICS ARCHITECT CLOUD DATA ENGINEERING DATA

PLATFORM MODERNIZATION MODERN DATA STACK

**************@*****.*** 917-***-**** Manhattan, New York, 10162 **************@*****.*** Profile

Accomplished Data Solutions Architect and Analytics Engineering Leader with more than 10 years of experience spanning data engineering, BI strategy, analytics modeling, and cloud platform architecture. Proven ability to modernize analytics environments, establish KPI frameworks, and implement enterprise-level data governance. Delivered scalable data solutions for SaaS, Healthcare, and FinTech organizations while maintaining strong security, compliance, and operational standards. Skilled in the modern data stack with expertise in dbt, Snowflake, Airflow, and Looker or Tableau, and known for enabling teams with reliable and high-quality datasets. Adept at aligning technical architecture with business needs, improving reporting efficiency, and supporting data-driven decision-making. Collaborative partner to product, engineering, and executive leadership teams. Recognized for strengthening data trust, streamlining analytics workflows, and building data systems that grow with organizational demands.

Skills

Data Architecture

enterprise system design

Cloud Warehouses

optimized analytics storage

Security & Compliance

HIPAA/SOC2/PCI frameworks

Lakehouse Architecture

hybrid analytical platformshybrid anal

Tech Leadership

mentoring & architecture decisions

ETL/ELT Development

structured data pipelines

Cloud Platforms (Mid-Level)

AWS/GCP/Azure usage

Data Governance

rules, standards, quality

API Integrations

ingestion from services

SQL (Basic Queries)

foundational data retrieval

BI Tools

basic dashboards & visuals

API Fundamentals

simple data extraction

Stakeholder Collaboration

clear communication skills

dbt (Advanced Modeling)

transformations & testing

Streaming Data Systems

real-time event pipelines

ML Data Pipelines

features & model support

Cost Optimization

lower compute & storage spend

Enterprise Data Strategy

long-term data planning

Workflow Orchestration

scheduled data automation

Data Modeling

star/snowflake structures

KPI Frameworks

metric design & tracking

Data Lake Concepts

storing large datasets

Python (Scripting Basics)

simple automation tasks

Data Visualization

charts, graphs, storytelling

Data Cleaning

removing errors & noise

Professional Experience

SENIOR ANALYTICS ENGINEER

Mux

•Developed scalable analytics models using SQL, dbt, and cloud warehouses to support reporting, experimentation, and AI initiatives.

06/2023 – Present

•Built and managed semantic layers, metrics catalogs, and reusable data assets to improve analytics consistency and speed.

•Implemented CI/CD pipelines, version control, and automated testing for analytics workflows ensuring high data reliability.

•Partnered with product managers, analysts, and data scientists to deliver business-critical datasets and dashboards.

•Authored detailed data documentation, playbooks, and modeling standards that improved team-wide productivity.

•Enhanced data model performance and reduced warehouse costs through query optimization and modular modeling.

•Drove stakeholder alignment by defining KPIs, tracking business metrics, and enabling self- service analytics across teams.

TECHNICAL LEAD – DATA SYSTEMS & ARCHITECTURE

The Modern Data Company

•Architected cloud-native data platforms leveraging modern data stack tools (dbt, Snowflake/BigQuery/Redshift, Airflow, Spark).

01/2021 – 06/2023

•Led engineering teams in designing scalable systems including real-time streaming pipelines, data lakes, and enterprise data warehouses.

•Established best practices for data modeling, pipeline development, documentation, and testing across the data organization.

•Implemented security, privacy, and compliance frameworks (HIPAA, SOC2, PCI) for sensitive and regulated data domains.

•Improved system performance and reduced cloud costs through optimized storage, compute tuning, and workload orchestration.

•Provided technical leadership across product, engineering, and analytics teams, influencing long-term architectural decisions.

•Mentored junior engineers, performed code reviews, and ensured engineering excellence and alignment with US industry standards.

SENIOR BI & DATA STRATEGY CONSULTANT

Databox

•Led full-cycle BI modernization initiatives for enterprise clients, transforming legacy reporting into modern, self-service analytics ecosystems.

07/2017 – 12/2020

•Defined KPI frameworks, governance models, and data strategies that improved decision accuracy and operational transparency.

•Delivered executive-facing dashboards (Power BI / Tableau / Looker) enabling data-driven decision-making across departments.

•Conducted data maturity assessments and recommended scalable analytics roadmaps aligned with business goals.

•Drove BI adoption, trained business teams, and improved data literacy across non-technical stakeholders.

•Identified data gaps and implemented MDM, lineage tracking, and governance controls to standardize data assets.

•Reduced reporting and analytics turnaround time by 40–70% through automation and workflow optimization.

Data Engineer

Mixpanel

•Designed and maintained scalable ETL/ELT pipelines in cloud environments (AWS/Azure/GCP) supporting enterprise analytics and machine learning workloads. 08/2014 – 06/2017

•Built automated data ingestion workflows using Python, SQL, and Airflow, improving pipeline reliability and reducing manual processing time by 60%+.

•Developed optimized data models and warehouse structures (Star/Snowflake) enhancing query performance and reporting efficiency.

•Implemented data quality frameworks and validation checks that reduced data inconsistencies and increased stakeholder trust.

•Collaborated with cross-functional teams to translate analytical requirements into robust technical solutions.

•Managed large batch and streaming datasets, ensuring efficient processing and low-latency delivery for business-critical systems.

•Improved data pipeline monitoring and alerting, reducing downtime and incident response times.

Projects

ENTERPRISE REAL-TIME FRAUD INTELLIGENCE & RISK SCORING PLATFORM FinTech Streaming Architecture Fraud & Risk Analytics Architected a high-performance, real-time fraud intelligence platform using Kafka, Snowflake, dbt, and Python to support large-scale financial transaction monitoring. Developed streaming ingestion pipelines, automated risk scoring workflows, and actionable dashboards for fraud operations. Enhanced detection capabilities, improved response times, and strengthened fraud prevention processes across critical payment systems. CLOUD DATA WAREHOUSE MODERNIZATION & ENTERPRISE BI TRANSFORMATION PROGRAM SaaS Modern Data Stack Architecture & Analytics Engineering Led the transformation of a SaaS organization’s analytics environment by implementing Snowflake, dbt, and Airflow to replace legacy reporting systems. Built automated ELT pipelines, established standardized KPI frameworks, and introduced a governed semantic layer. Significantly improved data quality, strengthened lineage visibility, and enabled organization-wide self-service analytics, resulting in faster insights and more reliable decision-making at the leadership level CLINICAL DATA INTEGRATION & HIPAA-COMPLIANT PATIENT ANALYTICS PLATFORM Healthcare Compliance & Governance EMR & Clinical Data Engineering Designed a secure, HIPAA-compliant analytics platform integrating EMR, claims, and clinical datasets via FHIR APIs, BigQuery, and Airflow. Implemented governed data models, standardized metrics, and scalable reporting layers that replaced manual workflows. Enabled faster clinical insights, improved operational readiness, and maintained strict compliance with healthcare data regulations.

Certificates

AWS Certified Data

Engineer – Professional

Snowflake SnowPro Core Google Cloud

Professional Data

Engineer (GCP PDE)

Education

Bachelors of Science

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