Move the Right Data,
Exactly Where It Needs to Go
StratApps designs, builds, and optimises enterprise ETL pipelines that eliminate data silos, reduce engineering debt, and deliver clean, trusted data to every team that depends on it.
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Strategy and Engineering for Every Data Movement Challenge
ETL consulting combines pipeline architecture expertise with hands-on implementation — ensuring your Extract, Transform, Load processes are reliable, scalable, and aligned with your analytical goals.
- Source system audit and connectivity mapping
- Transformation logic design and data quality rules
- Target schema and data warehouse modelling
- Orchestration, scheduling, and monitoring setup
- Performance tuning and error handling frameworks
- Runbook documentation and team enablement
Why Enterprise ETL Breaks Without Expert Guidance
Poorly designed pipelines don't fail loudly — they quietly deliver bad data until someone questions a dashboard at the worst moment.
Fragile, Hand-Built Pipelines
Scripts written to solve one problem accumulate into brittle infrastructure no single engineer fully understands — every schema change breaks something upstream.
Stale Data Reaching Analysts
Overnight batch jobs mean 9am decisions rely on yesterday's numbers — a delay that costs revenue in fast-moving markets.
No Lineage or Observability
When a metric looks wrong, nobody can trace exactly where in a 40-step pipeline the data diverged — debugging becomes a multi-day archaeology project.
Inconsistent Business Definitions
Sales, Finance, and Product each calculate "revenue" differently because transformations were written separately, without a governed semantic layer.
Scaling Hits a Wall
Pipelines built for 10 GB/day buckle when volumes grow 10x — re-engineering under pressure is far more expensive than designing for scale from the start.
Compliance Blind Spots
PII flowing through unmonitored pipelines creates GDPR and CCPA exposure — risks that only surface when an audit or breach forces the issue.
A Full Stack of ETL Data Integration Capabilities
ETL Pipeline Architecture and Design
Scalable, maintainable pipeline blueprints — source-to-target mapping, transformation strategy, orchestration framework selection, and data modelling for your target warehouse or lakehouse.
End-to-End Pipeline Implementation
Full-build delivery using best-fit tooling (dbt, Apache Spark, Airflow, Fivetran) — from initial extraction logic through to validated data landing in your warehouse.
Legacy ETL Modernisation
Assessment and migration of legacy SSIS, Informatica, or custom-script pipelines to modern cloud-native ELT architecture — with zero disruption to downstream consumers during transition.
Real-Time and Streaming Pipelines
Event-driven pipeline design using Kafka, Kinesis, or Pub/Sub for use cases where sub-hour data freshness is a business requirement, not an afterthought.
Data Quality and Governance Integration
Embedding quality checks, schema validation, lineage tracking, and PII handling directly into pipeline logic — so compliance and accuracy are built in from the start.
Pipeline Optimisation and Performance Tuning
Profiling and re-engineering slow or unstable existing pipelines — reducing run times, cutting compute costs, and improving SLA reliability for business-critical data flows.
From Discovery to Live Pipelines in Four Phases
A repeatable delivery framework that reduces risk, accelerates time-to-data, and produces pipelines your team can confidently own and extend.
Discover — Data Landscape Audit
We map every source system, assess data quality, document existing pipeline logic, and surface the gaps between what your data does now and what your analytics goals require.
Design — Architecture and Tooling Blueprint
We produce a detailed pipeline architecture — tool selection, transformation patterns, orchestration design, target schema, and data governance rules — before a line of code is written.
Build — Pipeline Implementation and Testing
Agile, sprint-based delivery of extraction, transformation, and loading logic — with unit tests, integration tests, and data validation gates at every stage to prevent bad data from progressing.
Deploy and Enable — Launch and Knowledge Transfer
Production deployment with monitoring, alerting, and runbook documentation — plus structured handover sessions so your internal team can confidently operate and extend the pipelines.
What Organisations Use ETL Consulting to Solve
Cloud Data Warehouse Population
Loading structured, transformed data into Snowflake, BigQuery, or Redshift from CRM, ERP, and transactional sources — ready for BI and self-serve analytics.
Analytics Pipeline Engineering
Building the data layer that powers executive dashboards, revenue reporting, and operational KPIs — with consistent definitions and reliable refresh cadences.
Data Lakehouse Ingestion
Designing raw-to-curated ingestion layers for lakehouse architectures on Databricks or Delta Lake — enabling both data science and BI workloads from a single source.
Operational Reporting Automation
Replacing manual spreadsheet exports with automated, scheduled ETL that feeds finance, supply chain, and operations reports — eliminating the weekly data-wrangling bottleneck.
Machine Learning Feature Engineering
Preparing and versioning training datasets and feature stores so ML teams receive clean, lineage-tracked inputs — shortening model iteration cycles significantly.
What Sets Our ETL Consulting Practice Apart
Architecture-First Mindset
We design before we build. Every engagement starts with a blueprint — so implementation is faster, cheaper, and produces systems that last beyond the project.
Tool-Agnostic Engineering
We recommend the right tool for your environment — not the one we happen to have a certification in. dbt, Spark, Airflow, Fivetran — we work across the full modern stack.
Embedded Quality Assurance
Data quality gates, schema tests, and anomaly detection are built into pipelines from day one — not added as an afterthought when bad data reaches production.
Knowledge Transfer Included
We document everything and train your team to operate what we build — no long-term dependency on an external consultant for day-to-day pipeline management.
Rapid Time-to-Value
Sprint-based delivery means your first pipelines reach production in weeks, not months — giving analysts access to clean data while we continue building the full solution.
End-to-End Data Practice
ETL sits inside a broader data and analytics capability at StratApps — so pipelines connect seamlessly to BI, ML, and data governance work if you need it.
StratApps redesigned our entire ingestion layer in eight weeks. What used to be a patchwork of overnight scripts is now a monitored, tested pipeline that our analysts actually trust. Dashboard refresh times dropped from 18 hours to under 30 minutes.
VP of Data Engineering — Global SaaS Platform, 1,200+ Employees
Common Questions About ETL Consulting
What exactly does an ETL consultant do?
How is ETL consulting different from ELT consulting?
How long does an ETL consulting engagement typically take?
How much does ETL consulting cost?
Which ETL and data integration tools do you work with?
Can you modernise our existing legacy ETL pipelines?
Ready to Build Pipelines Your Team Can Trust?
Book a free 45-minute ETL assessment. We'll review your current data infrastructure, identify the highest-impact pipeline gaps, and outline exactly how StratApps can help — with no obligation.
Book Your Free ETL Assessment No commitment required — scoping call included