Claude Code isn't autocomplete. It's the data architecture engine senior engineers now build around.
You've spent years earning trust through hand-built systems and painstaking design reviews. Data architecture used to take a separate career path to master. Now Claude Code compresses that path: senior engineers pick up dimensional modeling, ingestion design, and governance in a single day, and data architects use AI to move from hand-built pipelines to full platform designs in hours instead of weeks. This workshop teaches you that shift, whichever side of it you're standing on, before it becomes the baseline instead of the edge.
Workshop CompletedEighteen hands-on builds across six phases. One raw data source in the morning, a trusted star schema and live analytics by the end of the day.
Stand up a batch ingestion path with Claude Code directing source connection, schema detection, and load into a raw landing zone.
Point Claude Code at a raw dataset and generate a full profile: types, distributions, nulls, and outliers, before any cleanup begins.
Direct AI to surface the records that break the pattern: duplicates, drift, and outliers a manual scan would miss.
Have Claude Code infer validation rules straight from the data's own behavior instead of guessing them upfront.
Turn the exceptions the profiler surfaced into documented, reusable business rules your team can govern by.
Encode every discovered rule as versioned, reviewable YAML, quality checks that live in source control, not a wiki page.
Direct AI-generated transformation logic to standardize formats, fix values, and reshape fields at scale.
Run your YAML rules across the full dataset and get pass/fail results back in seconds, not a manual spot-check.
Wire quality checks directly into the pipeline so bad data gets caught and flagged automatically, on every run.
Take everything from profiling through validation and run it end to end on a full-scale, million-row dataset.
Let Claude Code identify redundancy and propose a normalized structure ready for warehouse modeling.
Design fact and dimension tables with AI reasoning through grain, keys, and relationships alongside you.
Assemble your fact and dimension tables into a full star schema, denormalized and built for fast analytical queries.
Normalize dimensions further into a snowflake design and know when that trade-off beats a star schema.
Lay out your warehouse for a columnar engine: partitioning, sort keys, and compression choices tuned for analytical scans, not row lookups.
Query your finished warehouse with AI assistance and surface insights ready for a business audience.
Auto-generate a data quality report summarizing every rule, exception, and fix applied across the day.
Chain every phase, profiling, rule discovery, cleansing, modeling, and reporting, into one AI-directed pipeline you take home.
Built from years architecting data systems. Keynotes and workshops, in-person or virtual, that leave you informed, capable, changed. Over 1,000 professionals across past workshops walked out doing things differently.
Eight capability domains. One production platform, built end to end with real data architecture. Built live, in one day.
Design end-to-end platforms with AI-assisted trade-off analysis: ingestion, transformation, and serving layers reasoned together.
Design and validate batch and streaming ingestion with Claude Code: CDC pipelines, schema drift detection, and source-to-lake orchestration, directed instead of hand-wired.
Direct agents to generate, tune, and validate query logic against execution plans, join order, index selection, cardinality skew, at a depth and speed manual review can't match.
Build dimensional models, fact-dimension schemas, and warehouse designs with architectural consistency across the full analytics layer.
Architect lakehouses, data warehouses, and cloud-native analytics platforms with documented patterns that hold up at enterprise scale.
Embed data quality checks, lineage tracking, and governance controls into platform design, not as an afterthought, but as architecture.
Move from data model to analytical dashboard faster, with Power BI and reporting workflows that Claude Code helps design and validate.
Generate data dictionaries, architecture docs, and decision records that stay current with your platform, without the manual maintenance burden.
One day separates the engineers who direct AI from the ones who explain why they didn't.
Your org has a hard technical problem. They call you, not because you're available, but because you solve it fastest. You design, validate, and document architecture in the time it takes others to schedule the meeting.
Sprint needs the system design by Friday? You ship Thursday. Analytics platform due next quarter? Architecture's ready next week. The person who makes the deadline leads the next one.
Most architects have opinions. You have artifacts: documented decisions, dimensional models, governance frameworks, data dictionaries, physical handbook. "I know how to do this" versus "here is how I did it."
You're not working longer. You're working differently. Your team notices. They start asking what changed. That question is worth more than any performance review cycle.
40 seats.
One cohort. Chennai.
The last workshop's early bird filled in 4 days; the payment link had barely been live 48 hours when the last seat went. The engineers and architects in this cohort will be operating at a measurably different level by Q3 planning season. The ones who wait will watch them land the strategic projects.
Early Bird is sold out. Standard pricing of ₹4,999 is now live for the next 10 seats. Cohort closes at 40.
This is not an introduction to data engineering. It is a precision workshop for senior professionals who already know how enterprise systems work and want data architecture fluency, with AI directing the heavy lifting. Junior engineers are not the audience.
Data architecture is the leverage skill your systems experience is missing. Claude Code compresses years of learning dimensional modeling and ingestion design into one day.
Who make cross-team technical decisions and need data platform trade-off analysis, storage, ingestion, modeling, in the same toolkit as their software judgment.
AI is the new leverage tool for the platform design work you already do. Move from hand-built pipelines to full platform designs in hours, not weeks.
Who build and operate pipelines and want to move from implementation to full architectural ownership, with AI handling the structural thinking.
Who evaluate platform decisions across software and data, and want data architecture fluency to move as fast as their software judgment already does.
Who lead engineering teams and want data architecture literacy to raise their team's platform decisions, not just their code.
Real feedback from a past Developer Road Ahead workshop.
Practical eye-openers for many Claude AI tools and tricks. The session pushed me to purchase a Claude Pro subscription and use it for my personal products. I followed up by attending the Agent harness session. Looking forward to the Claude Data Architect session.
Hands-on experience was great. It was great learning about skills, tools, and sub agents.
Architecture-first AI development, building maintainable codebases, and the importance of clear requirements, thinking beyond rapid development.
Spec-driven development using Claude, LLM integration, Skills usage, and Hooks.
Very nice and interactive.
Here is what this day is worth, line by line.
Senior software engineers, staff and principal engineers, data architects, data and analytics engineers, solution architects, and technical leads with hands-on experience building enterprise systems or data platforms. If you understand how real production systems behave and want to move faster without losing architectural depth, this workshop is for you.
None. You need strong engineering and architecture instincts. This workshop is about directing Claude Code with precision, using your domain expertise to guide AI toward better system and platform designs, not studying AI theory.
The workshop uses Claude Code as the primary tool. Architecture patterns, technical decision-making frameworks, and SQL engineering techniques transfer across software stacks, cloud platforms (AWS, Azure, GCP), and data warehouse technologies. Bring your laptop and a Claude subscription.
Architecture is a discipline that sharpens in rooms where engineers push back on each other's assumptions. The real value of this day is not the content alone; it's implementing real platform decisions with expert oversight in a space where every question gets a direct, technically honest answer. Online courses cannot replicate that.
Most of our events are free. This workshop is different: it is a full day of expert-led implementation with a small group deliberately limited to 40 people. The ticket price ensures every person in the room is invested and ready to work. You leave with architecture artifacts, templates, and a physical handbook that would cost significantly more to acquire separately.
Real implementation. Real enterprise scenarios. Real expert. 40 seats only.
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