Software Development Engineer · NYC

Building reliable, compliant data platforms on AWS.

I’m Joe Chamish, a Software Development Engineer focused on distributed systems, big data processes, and automation. I help teams ship faster while staying compliant and keeping infrastructure simple to operate.

Get in touch View LinkedIn
Amazon Big Data Technology · New York City Distributed Systems · Data Platforms · AWS

What I can help you with

  • Designing compliant, multi-tenant data platforms on AWS
  • Accelerating ML & analytics pipelines end-to-end
  • Automating internal workflows for finance & operations
  • Reducing infra cost with IaC and CI/CD

About Joe

I’m a Software Development Engineer based in New York City, currently working in Amazon’s Big Data Technology organization. My work sits at the intersection of distributed systems, data platforms, and operational excellence.

Practically, that means I design and build systems that let teams:

  • Access and process data safely across multiple tenants
  • Move from experiments to production ML faster
  • Automate complex business workflows with auditability
  • Operate infrastructure with confidence and less manual work

I approach engineering like I approached wrestling and chess: disciplined, strategic, and long-term focused. I care about architectures your team can maintain three years from now, not just quick wins today.

Snapshot

  • Role: SDE – Amazon Big Data Technology
  • Location: New York City, NY
  • Experience: 9+ years in backend & infra
  • Education: MS Computer Science, BS Computer Engineering (Binghamton University)
  • Certifications: AWS Solutions Architect Associate · AWS Developer Associate

What I’ve built and led

Software Development Engineer · Amazon Big Data Technology

New York City · Jan 2023 – Present

I design and implement multi-tenant data systems, governance controls, and integration layers that power analytics and ML workloads across Amazon.

  • Implemented fine-grained access control (FGAC) for internal multi-tenant data systems, strengthening EU DMA compliance and reducing cross-tenant data risk by ~25%.
  • Authored integration frameworks for EMR clusters with custom JARs in the internal data lake, enabling teams to trigger Spark jobs from Jupyter via Livy and speeding up AI/ML workloads.
  • Led cross-team integration of Amazon Big Data technologies into SageMaker Unified Studio, delivering a unified custom asset and accelerating model deployment pipelines by ~40%.
  • Developed PartiQL-based query overrides to normalize execution across Redshift, Trino, and Spark, allowing engine swaps without rewriting business logic.
  • Built custom ETL architectures for Amazon Transportation, improving data reliability and throughput while integrating with SageMaker and Lake Formation.

Software Development Engineer · Amazon Prime Video (Payments)

New York City · Sep 2022 – Oct 2023

I built automation around financial UAT workflows to reduce manual work for accountants and increase transparency around revenue processes.

  • Created a UAT automation platform for accountants, using GraphQL-based APIs to streamline validation workflows and cut manual effort by ~60%.
  • Built a GraphQL layer with AWS AppSync, Lambda, DynamoDB, and Step Functions to orchestrate multi-stage, auditable accounting workflows.
  • Designed DynamoDB data models and access patterns optimized for low-latency lookups and clear audit trails in accounting UAT.

Software Development Engineer · Amazon Prime Video (Localization)

New York City · Oct 2020 – Sep 2022

I led engineering for a content localization system that improved translation quality and dramatically reduced time-to-launch for new languages.

  • Lead engineer for Localization Quality Evaluator, an internal tool that detects and fixes translation issues across Prime Video content, processing around 10 million translated strings.
  • Managed a small team and collaborated with multiple partner teams, integrating with four services to add redundancy and minimize downtime.
  • Reduced time to launch new languages from ~8 weeks to ~8 days, enabling rollout to 32 languages in 2021.
  • Built end-to-end testing and automated rollback, maintaining ~99.8% uptime in 2022.

Software Engineer II · Trimble Maps

Princeton, NJ · Jul 2016 – Oct 2020

I focused on infrastructure as code, CI/CD, and cost optimization for mapping and logistics systems.

  • Built reusable Terraform modules to standardize infrastructure and reduce IaC duplication by ~30%.
  • Reduced on-prem compute costs by about 50% through improved Jenkins-based CI/CD pipelines.
  • Designed systems to promote artifacts and interact with them via RESTful APIs, tightening feedback loops between development and production.

Front-End Web Developer · Dashride

New York City · May 2014 – Jul 2016

I built interactive web interfaces for transportation workflows used by thousands of users.

  • Developed asynchronous, event-driven web pages that supported real-time usage by thousands of riders and operators.

Core skills & stack

Programming

Languages I use to build backend services, tooling, and CLIs:

  • Java · Python 3 · SQL
  • TypeScript · JavaScript
  • Bash · C++

Cloud & Infrastructure

Designing and operating systems on AWS:

  • EC2, S3, Lambda, ElastiCache
  • SageMaker, EMR, Step Functions
  • CloudFormation, AWS CDK, Terraform
  • Docker, CI/CD, Jenkins

Data & Storage

Databases and data platforms I work with:

  • PostgreSQL (incl. PostGIS)
  • DynamoDB · Aurora RDS
  • Redshift · Internal data lakes

Architecture & Specialization

Where I add the most value:

  • Distributed systems & data platforms
  • Multi-tenant, governance-aware architectures
  • Big data processing & ML pipelines
  • DevOps, observability, and automation

How this helps your team

If you’re a hiring manager, founder, or technical leader, here’s what working with me looks like in practice:

  • Clarity over buzzwords. I help you translate “we need a data platform” into concrete, achievable architectures and milestones.
  • Production from day one. I design systems with observability, rollout/rollback, and operational realities built in—not bolted on at the end.
  • Bridging teams. I’m comfortable talking with data scientists, finance stakeholders, and engineers, making sure systems match real-world workflows.
  • Long-term ownership. I optimize for architectures your team can maintain years from now, not just impressive diagrams.

Selected highlights

  • Cut multi-tenant data risk by ~25% through FGAC and governance improvements.
  • Accelerated ML model deployment by ~40% via SageMaker Studio integration.
  • Reduced new language launch time from ~8 weeks to ~8 days for Prime Video.
  • Helped drive ~60% reduction in manual UAT work for accountants.
  • Cut on-prem compute costs by ~50% using CI/CD and infra optimizations.

Get in touch & download

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