Drive end‑to‑end architecture for ingestion, transformation, analytics, and AI‑powered data products.
Set the standards, patterns, and roadmaps that shape our data future.
Build high‑performance ETL/ELT pipelines using AWS Glue, Python, and PySpark.
Craft serverless data services with Lambda, API Gateway & Step Functions.
Tune Athena, optimize S3 layouts, and lead complex data migrations like a pro.
Bring AI into real products: RAG pipelines, embeddings, inference endpoints, and more.
Partner with Data Scientists & ML Engineers to operationalize models with MLOps best practices.
Champion testing, data quality, observability, and lineage.
Enforce security‑by‑design with IAM, KMS, VPC endpoints, masking, and tokenization.
Mentor engineers, lead sprints, and elevate the team’s technical bar.
Work closely with Product, Security, and Architecture to turn ideas into reality.

13+ years in data engineering/backend engineering, including 4+ years leading technical teams and driving architecture decisions.
Deep, hands‑on expertise across AWS Data services & AI:
AWS Glue (Jobs, Crawlers, PySpark), Lambda (Python), Athena, S3, Glue Data Catalog
Python for data engineering (PySpark) and service development
ETL/ELT design patterns, orchestration (Step Functions / Airflow), and dimensional + Lakehouse modeling
Data migration strategies, validation frameworks, and rollback planning
Data lake architecture: Parquet, partitioning, with familiarity in Iceberg
IaC with Terraform / AWS CDK and CI/CD pipelines (CodePipeline, GitHub Actions, Azure DevOps)
Hands‑on experience with modern AI technologies and emerging AI tooling

Technical Project Manager

Key skills