Jose R. Dominguez Dev Services

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Scalable Software & Data Systems.
Built Right.

Development Services, Web applications, backend infrastructure, and analytic pipelines engineered for performance and growth.

Projects

Data Engineering & Pipeline Development

Design and implement scalable ELT/ETL pipelines that ingest, transform, and operationalize data from APIs, databases, and third-party platforms into analytics-ready systems.

Deliverables: Automated pipelines, data warehouses, transformation logic, scheduled workflows. Tech

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Cloud Data Platform Architecture

Build secure, production-grade data infrastructure on Azure and AWS, including relational databases, storage layers, and compute environments optimized for performance and scalability.

Deliverables: Cloud architecture, Azure SQL / AWS RDS deployments, storage design, infrastructure automation. Tech

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Analytics Dashboards & Business Intelligence

Develop executive-level dashboards and reporting systems that provide real-time visibility into operations, financial performance, and key metrics.

Deliverables: Tableau, Power BI, or custom dashboards; KPI frameworks; analytics data models. Tech

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Custom Web Applications & Backend Systems

Develop secure, scalable backend systems and full-stack applications using Django, FastAPI, ASP.NET Core, and modern cloud infrastructure.

Deliverables: Custom web platforms, APIs, authentication systems, database architecture. Tech

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API Integration & Workflow Automation

Integrate disparate systems and automate workflows across enterprise platforms such as Salesforce, cloud services, and internal tools to eliminate manual processes.

Deliverables: API integrations, automation pipelines, event-driven workflows, system synchronization. Tech

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Data Strategy & Technical Consulting

Advise organizations on how to structure, manage, and scale their data and software infrastructure to support growth, analytics, and product development.

Deliverables: Architecture plans, data models, system audits, implementation roadmaps. Tech

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Data Engineering & Pipeline Development

Overview

Build automated, production-ready data pipelines that reliably collect, transform, validate, and deliver data from APIs, databases, files, and third-party platforms into analytics-ready tables. The goal is to replace fragile spreadsheets and manual exports with repeatable workflows that are monitored, documented, and scalable.

Typical Use Cases

Daily/Hourly ingestion from REST APIs (pagination, retries, backoff, rate limits)
CDC-style refresh patterns (incremental loads, watermarking, idempotent runs)
Standardizing data into star schema / relational models for BI and reporting
Data quality rules (null thresholds, referential checks, anomaly detection)

Scope of Work

Source discovery & access setup (API keys, service principals, DB auth)
Ingestion design (raw landing zone → staging → curated models)
Transformations in Python/SQL (normalization, dedupe, type enforcement)
Scheduling + orchestration (cloud-native schedules / jobs)
Monitoring, alerts, logging, and run-history visibility

Deliverables

Production pipeline codebase (Python + SQL) with environment configuration
Structured warehouse tables (curated schemas, constraints, and documentation)
Automated scheduling (AWS/Azure) + error alerts and run logs
Data validation layer and pipeline health checks
Deployment guide + operator runbook (how to maintain and extend)

Outcomes (Business Value)

Faster reporting cycles

Data is refreshed automatically and consistently—no manual exports or merging.

Higher data trust

Validation rules and monitoring reduce surprises and downstream failures.

Scalable foundation

Curated datasets can power dashboards, apps, and analytics without rework.

Operational visibility

Run logs and alerts make failures actionable instead of silent.

Request

Cloud Data Platform Architecture

Overview

Design and deploy a secure, scalable data platform in AWS or Azure that supports analytics, application workloads, and operational reporting. This includes database selection, storage architecture, security controls, and environment setup to ensure performance and reliability from day one.

Architecture Components

Relational data layer (managed database deployments)
Storage layer (object storage, curated zones, backups)
Compute & job execution (scheduled tasks, batch compute)
Security posture (IAM/RBAC, secrets, network rules, encryption)
Observability (logging, metrics, access auditing)

Scope of Work

Requirements gathering (data volume, latency, SLAs, stakeholders)
Reference architecture + diagram (current state → target state)
Provisioning (database, storage, networking, identity access)
Performance considerations (indexing, partitioning, sizing)
Backup/restore strategy and disaster recovery planning

Deliverables

Deployed cloud environment (dev/prod separation where applicable)
Database + storage design (schemas, zones, lifecycle rules)
Security configuration (roles, policies, key management)
Architecture diagram + operational documentation
Runbook: provisioning, access, backups, and scaling guidance

Outcomes

Production-ready foundation

A clean cloud baseline designed for growth and stability.

Security and compliance alignment

Access controls, auditability, and encryption are designed in—not bolted on.

Better performance

Right sizing + indexing guidance avoids slow queries and runaway costs.

Lower operational risk

Backups, restore testing, and runbooks reduce downtime risk.

Request

Analytics Dashboards & Business Intelligence

Overview

Build dashboards and reporting systems that leadership can trust. This service covers KPI definition, data modeling, semantic layer design, and dashboard implementation with a focus on performance, clarity, and adoption.

What You Get

KPI catalog with definitions, filters, and calculation rules
Analytics-ready data model (facts/dimensions or reporting views)
Interactive dashboards (executive + operational views)
Role-based access and sharing setup
Performance tuning (query optimization, extract strategy where needed)

Typical Dashboards

Executive KPI overview (weekly/monthly trend + variance)
Operational pipeline / throughput (volume, cycle time, bottlenecks)
Financial performance (revenue, costs, margin, forecasts)
Data quality dashboards (freshness, missingness, anomalies)

Outcomes

Single source of truth

Consistent metrics reduce stakeholder debates and spreadsheet drift.

Faster decisions

Live dashboards replace manual reporting cycles.

Higher adoption

Simple, performant views increase usage and trust.

Reduced reporting burden

Automation eliminates recurring “can you pull this report?” requests.

Request

Custom Web Applications & Backend Systems

Overview

Build secure, scalable web applications and APIs designed around your workflows. This service covers application architecture, backend implementation, database design, authentication, and cloud deployment—with the goal of shipping software that performs reliably under growth.

Scope of Work

Backend architecture (services, modules, API boundaries)
REST API development (versioning, pagination, validation)
Authentication and authorization (RBAC, JWT/OAuth patterns)
Database design (schemas, indexing, constraints, migrations)
Deployment patterns (CI/CD, environment separation, secrets)

Deliverables

Production-ready web app or API (Django/FastAPI/ASP.NET Core)
Database schema + migration scripts
Authentication system + permission model
Cloud deployment configuration and operational notes
API documentation (endpoints, payloads, error codes)

Outcomes

Faster feature delivery

Clean architecture reduces friction when requirements evolve.

Security by design

Auth, access controls, and secrets are handled correctly from launch.

Scales with usage

Deployment and database choices support growth without rewrites.

Maintainable codebase

Documentation and patterns reduce long-term maintenance costs.

Request

API Integration & Workflow Automation

Overview

Connect systems and automate workflows so operations don’t depend on manual exports, copy/paste, or fragile scripts. This service covers API integration, event-driven processing, scheduled automations, and data synchronization between platforms (e.g., CRMs, databases, cloud services, internal tools).

Scope of Work

System integration design (source → transformation → destination)
API authentication (OAuth, tokens, service principals)
Reliable sync logic (retries, idempotency, dead-letter patterns)
Scheduling + monitoring (alerts on failure, run audit trails)
Error handling strategy (logging, payload capture, replay ability)

Deliverables

API integration implementation (endpoints, payload mappings)
Automated workflows (scheduled and/or event-driven)
System synchronization and reconciliation logic
Monitoring and error reporting setup
Integration documentation + support handoff notes

Outcomes

Operational efficiency

Automations remove recurring manual tasks and reduce cycle time.

Fewer data mismatches

Sync logic + reconciliation reduces inconsistencies across platforms.

More reliability

Retries, logging, and alerts turn failures into actionable tickets.

Better auditability

Run history and payload traceability support governance and debugging.

Request

Data Strategy & Technical Consulting

Overview

Clarify the technical strategy for your data and software systems. This service is structured as a short, high-impact engagement: assess the current state, identify risks and bottlenecks, and produce a clear roadmap for improving reliability, performance, and scalability.

What We Assess

Data architecture (sources, storage, modeling, governance)
Pipeline reliability (scheduling, monitoring, failure modes)
Database performance (indexing, query patterns, schema health)
Security posture (access controls, secrets management, least privilege)
Cost and scalability (right sizing, workload patterns, growth planning)

Deliverables

Current-state assessment + prioritized findings
Target-state architecture recommendations
Implementation roadmap (phased plan with milestones)
Risk register (what can break, how to mitigate)
Technical documentation package

Outcomes

Clear next steps

A roadmap that aligns engineering effort with business impact.

Reduced technical risk

Known bottlenecks and failure points are addressed proactively.

Higher ROI on engineering

Effort goes to high-leverage improvements, not random refactors.

Better stakeholder alignment

Teams share definitions, constraints, and success metrics.

Request

Ready to support your next project.

Open to collaboration and project inquiries.

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