You build the plumbing that makes everything else possible. If the data is wrong, no dashboard, no model, no insight downstream can be right. So we take this layer seriously.
What you'll work on
Data platforms on Databricks or Microsoft Fabric. Pipelines that move data from messy sources into clean, modelled, trustworthy outputs. dbt for transformations when it fits. Azure Data Factory or Fabric Pipelines for orchestration. Testing, monitoring, alerting, all the things that mean somebody's pager doesn't go off at 2am.
You'll work across industries: a different domain on the same week is normal. The technical patterns are similar; the business contexts aren't.
What you bring
Strong SQL. Comfortable in Python. Experience with at least one modern data platform (Databricks, Microsoft Fabric, Snowflake, BigQuery) and ideally dbt. Solid understanding of data modelling, partitioning, performance tuning. Architectural instincts: you can look at a half-built pipeline and tell where it'll break next year.
A baseline of software-engineering skills matters here more than in other data roles. Version control, code review, CI/CD, testing. Pipelines are code, and we treat them like it.
How we work
We code as agentically as we can. Claude Code, Cursor, Copilot, whichever tool fits. Pipelines, tests, documentation: AI shortens all of it. If you already work that way, great. If you don't yet, you'll pick it up here.
We pair with our clients' engineers, explain the trade-offs, and leave the platform in a state their team can maintain. The handover is the hard part of consulting, and we work hard at it.
What you'll get
A team that respects the foundation layer (rare in this business). Real growth, real ownership. Personal growth plan. Competitive pay.
Read the Plainsight playbook for the longer version of how we work.