Why join us
agileengine is an inc. 5000 company that creates award-winning software for fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and ai/ml, and our people-first culture has earned us multiple best place to work awards.
If you’re looking for a place to grow, make an impact, and work with people who care, we’d love to meet you!
About the role
as a cloud data architect, you’ll lead the design of a next-generation aws data platform from the ground up — building the medallion lakehouse architecture that will become the unified data foundation for the entire organization. This is a greenfield opportunity for a senior architect who wants genuine ownership: shaping ingestion patterns, governance frameworks, and scalable data models across s3, redshift, glue, dbt, and airflow.
What you will do
lead design and implementation of enterprise data architecture following medallion framework;
develop data models, pipelines, and schemas for data unification, governance, and analytics;
build and optimize aws‑based data infrastructure using core services;
implement lakehouse architecture integrating structured and unstructured data;
ensure performance, scalability, and cost efficiency of the data ecosystem;
design and oversee data ingestion from multiple on‑prem and cloud systems;
define integration strategies using batch, streaming, and event‑driven patterns;
collaborate with governance teams to enforce data security, access control, and quality;
work with engineering and business teams to deliver scalable data solutions;
support data platform modernization initiatives and roadmap execution;
document architecture, standards, and data flows for diverse audiences.
Must haves
8+ years of experience in data engineering or architecture;
5+ years of experience working with aws data ecosystems;
expertise with aws core services (s3, glue, redshift, lambda, athena, kinesis, emr);
experience with data integration tools (dbt, step functions, airflow, aws dms, kafka, kinesis);
strong knowledge of data modeling (medallion/lakehouse, dimensional modeling, data vault, kimball);
experience with infrastructure as code (terraform, cloudformation);
proficiency in python, sql, and spark (pyspark) for etl;
strong understanding of data governance, quality, and security;
experience with enterprise‑scale architecture and data integration;
nice to haves
practical experience and certification with boomi atomsphere.
Perks and benefits
professional growth: mentorship, techtalks, and personalized growth roadmaps.
Competitive compensation: usd‑based pay with education, fitness, and team activity budgets.
Exciting projects: modern solutions with fortune 500 and top product companies.
Flextime: flexible schedule with remote and office options.
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