Services
Six ways we take a data problem off your plate.
Each engagement usually touches more than one of these — discovery informs what gets built, and what gets built usually needs somewhere to keep running.
Process & Data Flow Discovery
Most data problems are described as technical, but they usually start somewhere else: a process that grew informally, a report nobody fully trusts, or a system nobody wants to touch. Before any of that gets automated, someone has to understand how the business actually works today.
What we do
- Stakeholder interviews
- Review of existing processes
- Data source inventory
- Process and system mapping
- Identification of manual steps and dependencies
- Failure-point analysis
- Data ownership and source-of-truth review
Examples
- A finance team's month-end close depends on four spreadsheets and one person's memory.
- Two departments report different numbers for the same metric and nobody knows which one is right.
- A vendor integration was built years ago and the person who built it has left.
Outcome: A clear, written picture of the current process, where it breaks down, and a recommended path to something more reliable.
Data Pipeline Engineering
Data needs to move from one place to another — a vendor API, an SFTP drop, a database, a report — and doing that by hand doesn't scale, and doing it with a fragile script doesn't last.
What we do
- API-to-database integrations
- Database-to-API integrations
- SFTP and file-based transfers
- CSV and flat-file processing
- Scheduled extraction and transformation
- Enrichment and aggregation
- Delivery to downstream systems and reports
Examples
- Pulling daily transaction data from a vendor API into an internal database.
- Delivering a nightly file to a partner in the exact format their system expects.
- Aggregating data from three internal systems into one reporting table.
Outcome: A pipeline that runs on schedule, handles failure gracefully, and doesn't require someone to babysit it.
Systems Integration
An ERP, a CRM, an accounting platform, a vendor portal, and a handful of internal databases all hold pieces of the same picture — but nothing was built to make them talk.
What we do
- Internal application integration
- Accounting and ERP system connections
- Vendor and market-portal API integration
- CRM data synchronization
- Custom database integration
- Cloud service connections
Examples
- Syncing customer records between a CRM and a billing system.
- Connecting a field-operations tool to internal scheduling and accounting systems.
- Pulling data from a vendor's portal that only exposes a login-gated UI.
Outcome: Information that moves automatically between systems, instead of being copied and pasted between them.
Reporting & Reconciliation Automation
Recurring reports are often produced manually, and the people producing them are also the ones who catch — or miss — the errors in them.
What we do
- Scheduled report generation and delivery
- Data aggregation across sources
- Reconciliation between systems
- Variance and missing-data detection
- Duplicate detection
- Exception reporting and automated alerts
Examples
- A daily reconciliation between an internal ledger and a vendor statement.
- A weekly operations report that used to take half a day to assemble by hand.
- Automated alerts when two systems' totals disagree by more than expected.
Outcome: Reports that are produced automatically and flagged automatically when something doesn't add up — the goal usually isn't another dashboard, it's not having to build the current one by hand.
Pipeline Reliability & Rescue
A script or integration exists and mostly works, but nobody fully understands it, nobody owns it, and everyone is a little afraid to touch it.
What we do
- Auditing undocumented scripts and jobs
- Fixing failing cron jobs and fragile Airflow DAGs
- Rebuilding unreliable vendor integrations
- Adding logging, retries, and monitoring
- Moving scattered credentials into proper secrets management
- Documenting ownership and behavior
Examples
- A cron job that fails silently once a month and nobody notices until finance asks.
- An Airflow DAG that's grown past the point anyone wants to modify it.
- A pipeline with no logging, so failures are diagnosed by guesswork.
Outcome: "Boring" here means predictable — a pipeline that behaves the same way every time, and tells you when it doesn't.
Managed Data Operations
Building a system is one project. Keeping it running as vendors change their APIs, credentials expire, and the business evolves is an ongoing responsibility — one that often has no clear owner.
What we do
- Monitoring and failure notification
- Retry handling for transient failures
- Response to vendor API changes
- Credential rotation support
- Schema change handling
- Ongoing data quality and reconciliation checks
- Maintenance and minor enhancements
Examples
- Getting notified — and fixing it — before a broken pipeline becomes a missed report.
- Updating an integration when a vendor changes their API without much notice.
- Rotating a certificate before it expires instead of after something breaks.
Outcome: A system that stays reliable as your business changes, without requiring you to build an internal team to watch it.
Under the hood
Technologies we work with
Languages
Python, SQL
Data
PostgreSQL, MySQL, SQL Server, SQLite
Integration
REST APIs, SOAP APIs, SFTP, CSV, JSON, XML, Webhooks
Orchestration
Airflow, Scheduled jobs, Event-driven workflows
Cloud / Infrastructure
AWS, Google Cloud, Containerized environments, Linux
Reporting / Processing
Pandas, Custom reporting workflows, Business system integrations
Need something simpler?
Simple problem? We have a simpler option.
Not every data problem needs a consulting engagement. SmallDataPipes is our managed service for straightforward recurring pipelines such as API pulls, SFTP transfers, file processing, scheduled exports, and routine data delivery.
Not sure which of these fits your problem?
That's what discovery is for. Tell us what's not working and we'll tell you what we think it needs.
Talk About a Data Problem