Your Data Infrastructure Partner.

    Data Infrastructure Engineering for teams whose databases, pipelines, and data platforms keep slowing down, costing more, or breaking. We trace the root cause, fix it, and stay on as your data infrastructure partner, not a one-time vendor call.

    Hands-on, cross-platform database expertise. Recent work for teams in insurance, manufacturing, transportation, and SaaS.

    We work hands-on with: PostgreSQL, Oracle, SQL Server, MySQL, MongoDB, Redis, AWS RDS & Aurora, Snowflake, BigQuery, Databricks, Kafka, Airflow, Terraform.

    Analytics and AI are only as good as the layer underneath.

    A database doesn't become slow overnight. Small architectural compromises accumulate for months until tuning stops helping and more cloud spend stops helping. The problem isn't performance. It's the decisions stacked underneath it.

    Database

    Queries that used to be fast start timing out. Connections run out. The answer becomes a bigger instance and a bigger bill.

    Platform

    Pipelines run green while data arrives late or incomplete. Every new dataset waits in a queue behind one overloaded team.

    Decisions

    Dashboards disagree, forecasts miss, and AI projects stall because nobody fully trusts the numbers underneath.

    We start at the bottom layer. That's usually where the problem started.

    Diagnosis first. Then a plan. Then a partner who stays.

    Every engagement begins with the same five steps, so you know what you'll have in hand before you commit to the next one.

    1. 01

      Diagnostic Call

      You describe what's breaking: slow queries, rising spend, pipelines that fail quietly, or numbers nobody trusts. We ask how the system got here.

      What you receive: A straight answer on whether we're the right team, and what an assessment would cover.

    2. 02

      Infrastructure Assessment

      We go through your actual setup: query plans, configuration, pipelines, and the access patterns behind them. Fixed scope, quoted before you commit.

      What you receive: A traced root cause, not a list of generic best practices.

    3. 03

      Findings

      A written report with the root cause, risk scores, and fixes ranked by impact and effort.

      What you receive: A roadmap your team can execute with us or without us.

    4. 04

      Implementation

      We ship the fixes, document the reasoning behind every change, and walk your team through it.

      What you receive: Working infrastructure and an engineering team that understands it.

    5. 05

      Support

      We stay on as your data infrastructure partner: watching the systems we changed, tuning as your data grows, and working alongside your team on what comes next.

      What you receive: A partner who already knows your infrastructure and is there when something shifts.

    How your data infrastructure partner actually works

    Engagements run in the open, inside the tools your engineers already use.

    • Direct engineer access

      The engineer tracing your problem is who you talk to. No account manager relaying it to whoever's actually staffed on it.

    • A shared channel with your team

      Questions, findings, and decisions happen in a shared Slack or Teams channel for the length of the engagement, not a ticket queue you have to follow up on.

    • Written findings, not slide decks

      Every recommendation comes with the evidence behind it: query plans, metrics, and the reasoning for the tradeoff we chose, not just the conclusion.

    • An incident war room when it matters

      When there's an active incident, we join a live call with your engineers and work it in real time, not a status update the next morning.

    • Full knowledge transfer

      Runbooks, architecture notes, and a walkthrough, planned in from day one instead of rushed at the end, so your team owns the system when we leave.

    Four ways to fix a data infrastructure problem

    Each option works for someone. Here's how they compare when the problem crosses the database, the pipelines, and the application.

    DharmOps

    Where it looksThe database, the pipeline, and the application code, together
    Ships the fixYes, with the reasoning documented
    Who you talk toThe engineer doing the work
    What stays behindRunbooks, architecture notes, and a full walkthrough
    CommitmentScoped to the problem, not a headcount or a contract

    Hiring a DBA

    Where it looksThe database, not the pipeline or the application
    Ships the fixYes, after weeks to hire and months to reach full speed
    Who you talk toYour employee, one person covering everything
    What stays behindKnowledge that leaves when they do, most of it never written down
    CommitmentA full-time salary, quiet quarter or not

    Large consultancy

    Where it looksSplit across separate practice teams
    Ships the fixSometimes, as a second statement of work
    Who you talk toAn engagement manager, relaying to whoever's staffed
    What stays behindA slide deck and a follow-on proposal
    CommitmentA multi-month statement of work, signed up front

    Monitoring tool

    Where it looksWhatever it's configured to watch
    Ships the fixNo, it tells you something's slow, not why
    Who you talk toA support ticket
    What stays behindDashboards, alerts, and more noise over time
    CommitmentAn annual license, renewing whether it caught anything or not

    Companies we've worked with

    "Our PostgreSQL queries were slowing down as our dataset grew. We'd already tried the obvious fixes ourselves. DharmOps got into our query plans, identified the root cause quickly, and tuned what mattered. The kind of deep database knowledge you can't easily find elsewhere."

    Jasara Technology Inc.

    PostgreSQL Query Optimization

    Questions engineering leaders ask first

    Tell us what's breaking.

    One call to walk through the symptoms. You'll leave knowing where to look first.

    Book a Discovery Call

    Or email contact@dharmops.com