Services
Data platforms, migration, governance, streaming, AI-ready data and cost optimization on AWS and Databricks, delivered by senior engineers and handed to your team.
Everything it takes to run trusted data on AWS and Databricks
Pick one service or combine them. Every engagement is led by senior engineers, delivered as code and handed over with documentation your team can use.
Lakehouses on AWS and Databricks
We design and build the foundation: storage layout on Amazon S3, open table formats (Delta Lake or Apache Iceberg), catalogs, compute and the bronze, silver and gold layers your analysts and auditors both understand.
What you get
- Reference architecture and decision records
- Workspaces, catalogs and storage defined in Terraform
- Ingestion and transformation pipelines with tests
- Monitoring, alerting and runbooks
Move platforms without breaking the business
EMR and Hadoop clusters, Glue jobs, on-premises warehouses or ageing ETL tools: we inventory what you have, migrate in waves, run old and new side by side and only cut over when the numbers match.
What you get
- Workload inventory and migration plan
- Wave-by-wave delivery with parallel runs
- Reconciliation reports before each cutover
- Decommissioning plan for the old platform
Access control, lineage and audit by design
We set up Unity Catalog and AWS Lake Formation so the right people see the right data: least-privilege grants, row filters and column masks, tag-based policies, lineage and audit trails that answer real questions.
What you get
- Catalog, schema and naming design
- Group-based permission model as code
- Fine-grained policies for sensitive columns
- Audit queries and access reviews
Streaming pipelines that stay correct
From Amazon Kinesis and Amazon MSK to Spark Structured Streaming and Lakeflow, we build streaming pipelines that handle late, duplicate and out-of-order events and can be replayed safely.
What you get
- Streaming architecture and service choice
- Exactly-once or idempotent processing design
- Backfill and replay procedures
- Latency and lag dashboards
Data foundations for RAG and agents
Retrieval and agents are only as good as the data behind them. We build governed document and table pipelines for Amazon Bedrock and Databricks Mosaic AI, with chunking, metadata, evaluation and cost tracking.
What you get
- Ingestion and freshness pipelines for knowledge
- Vector store and retrieval design
- Evaluation sets and quality metrics
- Access control that follows the source data
Faster jobs, smaller bills
We find where money and time actually go, using Databricks system tables, AWS Cost Explorer and query profiles, then fix the biggest items first: compute choices, table layout, job design and guardrails.
What you get
- Spend breakdown by team, job and table
- Ranked list of savings with effort estimates
- Cluster policies, budgets and tagging
- Before-and-after performance evidence
Simple ways to work together
Platform assessment
A short, fixed-scope review with written findings and a prioritized roadmap. Useful on its own, whoever builds next.
Project delivery
A small senior team delivers an agreed outcome in increments, working in your repositories and accounts.
Advisory & support
Architecture reviews, pairing and on-call guidance for teams that build themselves but want an expert nearby.
Not sure which service you need?
Describe the problem in a few sentences. We will tell you honestly where we can help, and where we cannot.