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Aditya Salabh

@adityasalabh

Data Engineer building production ETL/ELT and streaming pipelines on AWS, powering real-time analytics with strong data quality.

India

Message

What I'm looking for

I’m looking for a role where I can build production ETL/ELT and streaming pipelines on AWS/lakehouse tech, own data quality and observability, and work with real-time use cases that demand performance and reliable SLAs.

I’m a Data Engineer with 2.5+ years building production ETL/ELT and streaming pipelines on AWS. I’ve shipped data infrastructure for ad-tech aggregation (1M+ daily events), AI-driven compliance processing, and fraud detection—always with a focus on performance, reliability, and measurable outcomes.

In my recent roles, I built ingestion services against compliance REST APIs (Redis caching cut upstream calls 60% and reduced P95 latency from 3s to 500ms) and engineered an LLM-augmented extraction pipeline that processed 5K+ documents/day at 95%+ accuracy. I’m hands-on with lakehouse patterns (Apache Iceberg, S3 Tables, dbt) and real-time systems (Kafka, Spark Structured Streaming, Airflow), and I’m excited to grow in teams that value data quality, testing, and production-ready engineering.

Experience

Work history, roles, and key accomplishments

Software Engineer (Data Infra)

Zerberus Technology

Feb 2025 - Sep 2025 (7 months)

Built an ingestion service against compliance REST APIs, using Redis caching to cut upstream calls by 60% and reduce p95 latency from 3s to 500ms while sustaining 10K+ requests/day. Engineered an LLM-augmented pipeline to extract structured records from unstructured compliance documents, processing 5K+ docs/day at 95%+ accuracy and reducing manual labeling effort by 70%.

Redis Data Ingestion Data Structuring Accuracy Quality Optimization LLM LLMs (LangChain Snowflake S3 Airflow Kafka Kafka Streams

Data Engineer (Associate)

Taiyo.AI

Aug 2024 - Nov 2024 (3 months)

Optimized ETL pipelines across 5+ datasets using PySpark and Pandas, reducing processing time by 35% and improving SLA to 98%+ while validating 2M+ daily records. Automated AWS-based ingestion (S3, Lambda) with Docker and added error handling/validation to cut deployment time by 50%.

Pyspark Pandas ETL Data Validation AWS S3 AWS Lambda Docker Error Handling Data Ingestion

Backend Developer (Data)

Xamtac Consulting

Feb 2023 - Aug 2024 (1 year 6 months)

Built a multi-source data extraction system aggregating Google Ads and Meta APIs, transforming 1M+ daily events into Django dashboards with 99.9%+ reliability. Orchestrated 40+ AWS EC2 pipeline refreshes, reducing manual refresh time by 40% and eliminating weekend on-call, while implementing transformation logic and data quality checks to catch 99%+ anomalies.

Data Extraction AWS EC2 data transformation Data Quality Query Optimization Remote Python Redshift S3 S3 Lambda Remote

Education

Degrees, certifications, and relevant coursework

CloudyML

Advanced Data Engineering Bootcamp (with Internship), Data Engineering

2025 - 2026

Activities and societies: Capstone: end-to-end production ELT pipeline on AWS (3M+ rows, Iceberg, Airflow, dbt, lakehouse architecture). Internship: Kafka streaming pipeline to S3/Parquet/Hive with Athena + QuickSight insights.

Completed the CloudyML Advanced Data Engineering Bootcamp with internship experience, including an end-to-end production ELT pipeline capstone on AWS.