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.
Why join us
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 data engineer, you’ll be part of a small, senior team building a cloud-native data platform on aws from the ground up — moving raw data through bronze, silver, and gold layers into clean, trusted, analytics-ready datasets that directly power business decisions. Working closely with the data architect and head of data, you’ll have real visibility into the full data lifecycle: pipeline design, data quality, governance, and delivery. If you want a role where your engineering work is foundational rather than incremental, and where the stack — s3, glue, redshift, dbt, airflow, pyspark — is genuinely modern, this is it.
What you will do
build and maintain scalable etl and elt pipelines across aws services;
implement medallion architecture for data ingestion, transformation, and delivery;
collaborate with data architects on data modeling and schema design;
develop ingestion frameworks for structured, semi-structured, and streaming data;
integrate data quality, lineage, and observability into pipelines;
work with analytics and business teams to deliver consistent and well-documented data;
write clean and testable python and sql code following best practices;
support data governance and security standards including compliance requirements;
monitor pipeline performance, troubleshoot issues, and optimize scalability and cost efficiency.
Must haves
5+ years of experience as a data engineer working with aws data ecosystems;
strong experience with aws services (s3, glue, lambda, kinesis, redshift, athena, step functions);
proficiency in python, pyspark, and sql for data transformation;
strong understanding of etl design patterns, batch and streaming data processing;
knowledge of data modeling (star schema, snowflake schema, incremental processing);
experience with orchestration tools (airflow, step functions, dbt);
understanding of data governance, data quality frameworks, and ci/cd for pipelines;
experience working in agile, cross-functional environments;
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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