Alter Domus
№ 01 — 3 roles
Data Engineer IMarch 2026 - Present
- Reduced pipeline execution time by up to 60% by optimizing critical ETL/ELT workloads across AWS, Databricks, dbt, and Airflow through SQL tuning, DAG refactoring, Airbyte incremental syncs, and parallelism improvements
- Drive end-to-end delivery of high-impact data pipelines on the financial data platform, expanding scope across AWS Athena, MWAA, Airbyte, Databricks, and PostgreSQL
- Partner directly with business and product stakeholders to elicit requirements and translate them into reliable data products, using AI agents (Amazon Q Developer, Claude Code, Databricks Genie) and MCP-based tooling to accelerate requirement discovery, data exploration, and execution
- Advance DataOps and DevOps maturity through GitHub Actions CI/CD, Terraform-managed infrastructure, automated dbt tests, and SLAs on Airflow pipelines, raising platform reliability and deployment velocity
- Own cross-functional delivery within Agile (Jira, GitHub) and present technical solutions in engineering reviews, increasing visibility of data platform work across analytics, product, and DevOps partners
Associate Data EngineerJune 2025 - March 2026
- Independently owned end-to-end ETL/ELT pipeline development across multiple source systems, shipping production-grade Python, SQL, and dbt code on the AWS and Databricks data platform
- Expanded ingestion coverage by building and maintaining Airbyte and Airflow pipelines on AWS MWAA, onboarding new data sources and reducing manual data wrangling for downstream analysts
- Developed and tuned dbt models and complex SQL transformations against AWS Athena, Databricks, and PostgreSQL, improving data quality and query performance for financial reporting use cases
- Partnered directly with analysts and business stakeholders to translate requirements into data models, using AI copilots (Amazon Q Developer, Claude Code, Databricks Genie) to rapidly prototype, refactor, and harden pipeline logic
- Strengthened DataOps practices through GitHub-based CI/CD, peer code reviews, automated dbt tests, and Airflow observability, increasing release confidence and deployment cadence
- Contributed to sprint planning and cross-team design discussions in Jira, growing visibility across engineering, analytics, and DevOps partners
Data Engineer InternMarch 2024 - June 2025
- Ramped up on the financial data platform architecture, learning internal data models and ETL/ELT patterns across the AWS-based modern data stack
- Built and tested initial dbt models and Python-based pipeline components under senior engineer mentorship, contributing to production releases
- Wrote and optimized SQL queries for data validation and exploratory analysis on AWS Athena, Databricks, and PostgreSQL
- Assisted in deploying and monitoring Apache Airflow DAGs on AWS MWAA and configuring Airbyte connectors, gaining hands-on cloud orchestration experience
- Leveraged AI assistants (Amazon Q Developer, Claude Code) to accelerate onboarding, understand legacy code, and translate business requirements into working pipeline components
- Participated in Agile ceremonies and contributed to sprint deliverables using Jira and GitHub workflows