Bangalore, India • Shipping data platforms since 2012 • Building with AI, building for AI
flowchart LR
A[("SOURCES<br/>Kafka · APIs · S3")]
B["INGEST<br/>Flink · Spark · Glue"]
C["ORCHESTRATE<br/>Airflow 3.x · MWAA"]
D[("LAKE<br/>Iceberg · S3 · MinIO")]
E["QUERY<br/>Trino · Athena · DuckDB"]
F(["AI LAYER<br/>LLM tooling · RAG · Bedrock"])
G[["PRODUCTS<br/>dashboards · features · agents"]]
A --> B --> C --> D --> E --> G
D -.-> F -.-> G
C -.-> F
classDef ai fill:#2D1B4E,stroke:#8957E5,stroke-width:2px,color:#E6EDF3;
classDef core fill:#161B22,stroke:#30363D,color:#E6EDF3;
class F,G ai;
class A,B,C,D,E core;
The solid path is where I've lived for a decade. The dotted path is where I'm building next.
| Platform work | Airflow 3.x · Kubernetes · Iceberg + Trino lakehouse patterns |
| AWS | MWAA · EMR · Glue · Athena · S3 · Lambda · ECS |
| AI in the loop | Using AI across the dev cycle — design, code, review, docs |
| AI in the product | Shipping features where AI measurably improves UX |
| Learning | AWS Data Engineer cert · Go for backend services · model serving |
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local-infra-setup Local dev infra with all services wired together. Shell · Docker · Makefile
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airflow3-dags Production-style DAG patterns exploring Airflow 3.x. Python · Airflow 3.x
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| ORCHESTRATION |
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| AWS |
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| INFRA |
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| LANGUAGES |
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| DATA |
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| AI / ML |
upskilling →
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Airflow DAG patterns at scale Internal tech talks — production-grade orchestration, failure modes, observability. Data platform case studies Lakehouse architecture, cost/perf trade-offs. Available on request. → Invite me to speak |
Airflow community Contributing around Airflow 3.x patterns, providers, and dev ergonomics. Local-dev tooling local-infra-setup — batteries-included dev stack. → All repositories |
Production DAG patterns Notes on idempotency, backfills, and observability in Airflow. AI-augmented engineering What actually moves the needle in the daily dev loop. → Posts on LinkedIn |
Apache Airflow · Data pipeline design · Kubernetes for data · Data lake architecture · AWS data stack · AI-augmented development · Shipping AI features in data products