Data Engineering
Data Engineering Services That Turn Scattered Data Into Reliable Pipelines
Oklahoma Data Partners designs, builds, and monitors the pipelines that move, clean, and connect your business data — turning scattered sources into reliable, automated, decision-ready data. Senior, specialist-led expertise without the cost of a full-time hire. Based in Oklahoma City, OK, Oklahoma Data Partners serves the Oklahoma City–Tulsa region and supports teams locally across Oklahoma. Data engineering builds and operates the pipelines that load a warehouse; warehouse architecture and target design are separate decisions. See how broken data pipelines undermine dashboard trust.
Priority and after-hours support available by plan.
Pipeline Operations
adf-prod · 14 pipelines
Records today
1.24M
Pipelines passing
98%
Avg refresh
4.2 min
Data quality
99.4%
Throughput (k rows/min)
12.6k/minData quality
Live pipeline runs
sales_etl · loaded
CRM → warehouse · 184k rows
finance_api_sync · loaded
ERP → staging · 52k rows
inventory_load · running
SFTP files → warehouse
marketing_files · retried
auto-recovered in 38s
Rows by source (k)
Sound familiar?
The data problems that quietly slow your business down
None of these look like a single dramatic failure — they erode trust, speed, and confidence in your numbers a little at a time.
Hours lost to manual reporting
The same spreadsheets get rebuilt by hand every week — copy, paste, reconcile, repeat — instead of refreshing on their own.
ETL jobs that break silently
A pipeline fails overnight, no one is alerted, and the first sign of trouble is a number that looks wrong in a meeting.
Slow, late data refreshes
Dashboards lag hours or days behind reality, so decisions get made on stale numbers nobody fully trusts.
Inconsistent definitions
“Revenue” means one thing in one report and something else in another, and reconciling them eats entire afternoons.
Disconnected systems
Your CRM, ERP, finance tools, and files all live on islands, so nobody has a single, joined-up view of the business.
Poor data quality
Duplicates, missing values, and unvalidated inputs quietly corrupt reports until the data itself stops being believed.
What we do
End-to-end data engineering
From first connection to ongoing monitoring — one team that builds, cleans, automates, and looks after the pipelines your business runs on.
ETL & ELT Pipelines
Robust extract, transform, and load pipelines that move data dependably from source systems into a clean, query-ready warehouse.
Build a pipelineAzure Data Factory
Orchestrated, scheduled, and monitored data flows in Azure Data Factory — built to scale and recover from failures gracefully.
Orchestrate in ADFSSIS Development & Modernization
New SSIS packages and modernization of legacy ones — migrating fragile, hand-built flows into maintainable, documented pipelines.
Modernize SSISAPI Integrations
Connect CRMs, ERPs, finance tools, and SaaS platforms through their APIs so your data flows automatically instead of by hand.
Connect an APIFile Ingestion Automation
Automated ingestion of CSV, Excel, and flat files from email, SFTP, or cloud storage — validated and loaded without manual steps.
Automate ingestionSQL-Based Transformations
Clean, well-structured SQL transformation logic that standardizes, joins, and shapes raw data into trustworthy models.
Shape your dataData Quality Checks
Validation rules, deduplication, and reconciliation built into the pipeline so bad data is caught before it reaches a report.
Add quality checksWarehouse Loading
Reliable loading into SQL Server, Azure SQL, Snowflake, or your warehouse of choice, modeled for fast, consistent reporting.
Load the warehouseCloud Data Movement
Secure movement of data between on-prem and cloud, and between cloud platforms — with the right cadence for your business.
Move to cloudData Pipeline Monitoring
Proactive monitoring and alerting that catches failed jobs, late loads, and anomalies before your team ever notices.
Monitor pipelinesHow your data flows
From scattered sources to confident decisions
We connect every source, transform and validate the data, then land it where your dashboards can trust it — automatically, on schedule.
Source Systems
CRM · ERP · finance
APIs · Files · DBs
Extract & collect
ETL / ELT
Transform & clean
Data Quality
Validate & dedupe
Data Warehouse
Modeled & stored
Power BI
Dashboards & reports
Decisions
Confident action
Tools & platforms
The data stack we work with every day
Deep, hands-on experience across the Microsoft data platform and the modern cloud warehouse ecosystem.
What you get
Pipelines you own, not black boxes
Every engagement leaves you with working, documented, monitored data infrastructure — plus a clear scorecard of how reliable it is.
A working data pipeline
An automated, scheduled pipeline running in your environment — not a prototype that only worked on our laptop.
Source-to-target data mapping
Clear documentation of where every field comes from, how it is transformed, and where it lands.
Error handling & retries
Pipelines that fail safely, retry sensibly, and tell someone when a job genuinely needs attention.
Data validation rules
Built-in checks for duplicates, missing values, and bad inputs so quality is enforced, not assumed.
Documentation & handover
Plain-language documentation of how the pipeline works, so your team is never locked out of its own data.
A monitoring plan
Alerting and a simple operational runbook so failed jobs and late loads surface early — not in a meeting.
Sample pipeline scorecard
Every engagement ends with a score like this — a clear, prioritized read on where your pipelines are strong and where they need attention.
The difference
From manual chaos to automated confidence
Before Oklahoma Data Partners
Manual & brittle- Reports rebuilt by hand every single week
- ETL jobs that fail silently overnight
- Dashboards hours or days behind reality
- Metrics that never quite reconcile
- Systems that don't talk to each other
- Data nobody fully trusts to act on
With Oklahoma Data Partners
Automated- Pipelines that refresh automatically on schedule
- Failed jobs caught early with proactive alerts
- Near real-time data flowing to dashboards
- One consistent definition for every metric
- Connected systems with a single source of truth
- Clean, validated data leadership can rely on
Data quality
We turn unreliable data into data you can trust
Bad data quietly corrupts every report downstream. We build quality into the pipeline so it is enforced automatically — not hoped for.
Common data quality issues
The riskDuplicate records
The same customer, order, or transaction counted twice — quietly inflating every number downstream.
Missing values
Blank fields and gaps that break joins, skew totals, and make reports impossible to fully trust.
Inconsistent definitions
The same metric calculated differently across teams, so no two reports ever quite agree.
Failed transformations
Logic that breaks on edge cases and silently drops or mangles rows before anyone notices.
Late refreshes
Loads that finish hours behind schedule, leaving dashboards showing yesterday's reality.
Unvalidated data
Raw inputs that flow straight into reporting with no checks, so errors compound over time.
How Oklahoma Data Partners fixes it
Built inValidation rules
Automated checks that reject or quarantine bad rows before they ever reach the warehouse.
Standardized transformations
Consistent, documented SQL logic so every metric is calculated one trusted way.
Error handling & retries
Pipelines that recover from failures and escalate only the problems that truly need a human.
Monitoring & alerting
Proactive alerts on failures, late loads, and anomalies so issues are caught early.
Clear documentation
Source-to-target mapping and runbooks so your team always understands its own pipelines.
Clean warehouse tables
Deduplicated, validated, well-modeled tables that reporting tools can trust by default.
Why Oklahoma Data Partners
Senior data engineers who build pipelines you can actually trust
No junior hand-offs and no black boxes. You work directly with experienced engineers who design for failure, validate the data, and document everything they build — so your pipelines get more dependable over time, not more fragile.
- Specialist-led delivery — you work directly with senior engineers
- Pipelines built to fail safely, retry, and alert
- Validation and reconciliation built into every flow
- Plain-language documentation and a full handover
End-to-end
pipelines built, monitored, and documented
100%
of pipelines ship with validation built in
Automated
refreshes that replace manual reporting
By plan
priority & after-hours support available
Ways to work together
Engagements that fit how you need help
Whether you need an honest baseline, a single pipeline built, a fragile system modernized, or dependable ongoing coverage, there is a clear way to start.
Pipeline Assessment
Teams who want an honest baseline of how their data flows today.
- Source & system inventory
- Data quality review
- Pipeline & refresh audit
- Prioritized findings report
Best fit: A clear first step or second opinion
Book an AssessmentData Pipeline Build
Teams with a specific pipeline or integration to stand up.
- ETL / ELT design & build
- Source-to-target mapping
- Validation & error handling
- Documentation & handover
Best fit: A defined, scoped pipeline project
Scope a BuildETL Modernization Sprint
Teams with fragile, legacy, or hand-built pipelines to fix.
- Legacy SSIS / job review
- Refactor to maintainable flows
- Reliability & monitoring upgrades
- Before / after benchmarks
Best fit: Replacing brittle, aging pipelines
Start a SprintMonthly Data Engineering Support
Teams that need dependable, ongoing pipeline coverage.
- Pipeline monitoring & alerting
- Maintenance & enhancements
- New source onboarding
- Priority and after-hours support available by plan
Best fit: Continuous, hands-on coverage
Get Ongoing SupportQuestions, answered
Data engineering FAQ
Turn scattered data into reliable pipelines.
Start with a conversation about your data and systems, and get a clear, honest path from manual reporting to automated, trustworthy pipelines.
Priority and after-hours support available by plan.
Security & confidentiality
Your data environment is treated with care.
We treat database, reporting, and analytics environments as sensitive — and handle every engagement with professionalism, discretion, and respect for your systems.
Respect for internal systems
Careful access handling
Security-aware recommendations
Confidential conversations
Documentation discipline
Business-sensitive reporting awareness