Data platforms and analytics that decide
US-based data engineers building warehouses, pipelines, and BI stacks that turn raw operational data into decisions.
Data and analytics engineering turns scattered systems into one trustworthy warehouse. NextGen builds ELT pipelines, dbt models, and Snowflake/BigQuery/Postgres warehouses with dashboards your executives actually use. Most warehouse builds run $60K-$250K and deliver first usable dashboards inside 6 weeks.
What this service delivers
NextGen Coding Company builds modern data platforms — warehouses, pipelines, transformations, and BI — that make data usable at the pace decisions actually need. Our engineers ship Snowflake, BigQuery, dbt, Fivetran, and Looker or Metabase stacks that scale with the business.
Analytics is only as good as the plumbing beneath it. NextGen builds the plumbing with software engineering discipline — testing, code review, IaC, and observability — so dashboards and models can be trusted.
Why choose NextGen Coding
We treat data pipelines like production code — versioned, tested, monitored, and reviewed. That's what separates data that ships from data that stalls.
US-based data engineers who work in your stack — dbt, Airflow, Snowflake, BigQuery, Databricks, Redshift, Fivetran, Stitch, Looker, Metabase, Superset.
Cross-trained with our AI and full-stack engineers, so data investments feed AI features and product analytics — not just BI dashboards.
Built for teams that need to move
SaaS Platforms
Product analytics, cohort analysis, and revenue reporting on modern warehouses.
Ops-Driven Businesses
Operations and finance teams building single-source-of-truth reporting.
PE Portfolios
Portfolio companies needing standardized KPI reporting across the portfolio.
Marketing & Growth
Attribution, LTV, and CAC modeling with warehouse-native tooling.
Data Modernization
Teams migrating from legacy BI or Excel-driven reporting to modern stacks.
AI-Ready Data
Data foundations built for AI, RAG, and ML workloads on top of them.
Everything included in a NextGen build
Data Warehousing
Snowflake, BigQuery, Redshift, and Databricks architected for cost and query performance.
ETL / ELT Pipelines
Fivetran, Stitch, Airbyte, and custom pipelines with dbt transformations.
dbt Modeling
Modular, tested, documented dbt projects with staging, marts, and metrics layers.
BI & Dashboarding
Looker, Metabase, Tableau, PowerBI, and Superset dashboards tied to modeled data.
Reverse ETL
Hightouch and Census wiring warehouse data back into product and GTM tools.
Data Quality & Observability
Great Expectations, Monte Carlo, and dbt tests wired into CI.
Product Analytics
Amplitude, Mixpanel, and Segment implementation with event schema governance.
ML & Feature Stores
Feature engineering, training data pipelines, and vector stores for AI workloads.
How the engagement runs
Data Audit
Map data sources, current stack, reporting needs, and highest-value gaps.
Warehouse & Pipeline Design
Recommend warehouse, ingestion, and transformation architecture.
Model & Instrument
Build dbt models, event tracking, and metrics layers with tests and docs.
BI Rollout
Stand up dashboards, enable self-service, and train stakeholders.
Governance
Data quality tests, documentation, and observability wired into CI.
Ongoing Data Ops
New sources, new models, and continuous improvement as the business evolves.
Transparent, US-market pricing
Data Engineer
Dedicated US-based data engineer, from $14K/mo.
Data Pod
Multi-engineer pod for warehouse migrations and platform builds.
Data Stack Sprint
6–10 week fixed-scope engagement to stand up a modern data stack.
All pricing is transparent and US-market calibrated. We don't compete on the lowest upfront number — we compete on delivering outcomes that generate the highest return on investment.
Results our clients experience
Single Source of Truth
Finance, ops, and product agreeing on numbers for the first time — because everything runs off one modeled layer.
Faster Reporting
Weekly reports moved from manual spreadsheets to auto-refreshed dashboards.
AI-Ready Foundations
Data platforms that immediately support RAG, ML, and internal AI copilots.
Warehouse Cost Cuts
Query optimization and materialization strategies cutting Snowflake and BigQuery spend meaningfully.
Thought leadership & technical writing
The Modern Data Stack, Honestly
What's worth adopting, what's overhyped, and how to sequence the stack for your stage.
dbt at Scale
Modeling patterns, macro strategies, and testing that scale beyond your first 100 models.
Warehouse Cost Engineering
Practical patterns to cut Snowflake and BigQuery bills without breaking reporting.
Objections, addressed
We already have dashboards — do we need this?+
The question is whether they're trusted, tested, and maintained. Most dashboard estates have coverage but not trust — that's the gap we close.
Snowflake and dbt are too expensive.+
For most mid-market and up, they're cheaper than in-house data engineers doing worse work. Cost engineering is part of every engagement.
We already have a data engineer.+
Great — we augment. Most in-house teams welcome senior capacity for warehouse migration or dbt scale-up.
We're too small for a real data stack.+
Then we scope small. Metabase + Postgres + Airbyte is a real stack — sequencing matters more than tool choice.
Frequently asked questions
Which warehouses do you work with?+
Snowflake, BigQuery, Redshift, Databricks, and Postgres for smaller footprints.
Do you do dbt?+
Yes — dbt is a core competency. Modular projects, testing, documentation, and CI.
Do you handle product analytics?+
Yes — Amplitude, Mixpanel, Segment implementation with event schema governance.
Can you help with data governance?+
Yes — documentation, ownership, access controls, and lineage tooling.
Do you build ML features?+
Yes, with our AI engineering practice — feature stores, training pipelines, and vector stores.
Engineering discipline. US-based delivery.
NextGen Coding Company builds modern data platforms with software engineering discipline. US-based team with credentials from Columbia, Harvard, Oxford, Apple, Citi, and Wells Fargo.
Our data team is entirely US-based, serving clients nationwide. Governance conversations, model design reviews, and stakeholder training all benefit from a team in your time zone.
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