The Role
Architect, build, and scale a modern data platform: design production ETL/ELT pipelines, optimize Snowflake schemas, orchestrate workflows (Airflow/Prefect/Dagster), integrate APIs and event streams, implement data quality, lineage, and alerting, and apply CI/CD, Docker, IaC, and automated testing to ensure reliable, accessible data.
Summary Generated by Built In
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
We are looking for a Senior Data Engineer to architect, build, and scale a modern data platform — designing production-grade ETL/ELT pipelines, optimizing Snowflake data warehouse schemas, and establishing robust DataOps practices. You will orchestrate workflows using Airflow, Prefect, or Dagster, implement data quality and lineage frameworks, integrate third-party REST APIs and event-driven sources, and apply software engineering standards including CI/CD, Docker, and automated testing to data repositories. The role prioritizes clean, well-tested Python code and a deep commitment to data reliability and accessibility.
WHAT YOU WILL DO
- Design, build, and maintain reliable, scalable ETL/ELT workflows that process batch and streaming data from diverse sources;
- Design production-ready normalized and denormalized schemas in Snowflake to optimize query performance and support enterprise analytics;
- Connect and ingest data from third-party REST APIs, event-driven streams, and batch sources into core data storage platforms;
- Maintain and expand workflow orchestration pipelines using Airflow, Prefect, or Dagster;
- Implement automated data testing, validation, lineage tracking, and proactive alerting frameworks to ensure data accuracy and system uptime;
- Drive CI/CD best practices, maintain codebases using Git and Docker, and adopt Infrastructure-as-Code patterns;
- Apply modern software engineering standards, including design patterns, automated unit and integration testing, and clear documentation.
MUST HAVES
- 4+ years of experience as a Data Engineer;
- Strong proficiency in Python, including modular, maintainable, and well-tested code;
- Advanced knowledge of SQL, query optimization, database design principles, and normalization/denormalization patterns;
- Hands-on experience with Snowflake;
- Production experience with workflow orchestration tools such as Apache Airflow, Prefect, or Dagster;
- Experience working with REST APIs, event-driven architectures, and batch and streaming pipelines;
- Experience implementing automated data quality checks, data lineage, and alerting mechanisms;
- Strong experience with Git, Docker, CI/CD automation, and Infrastructure-as-Code fundamentals;
- Upper-intermediate English level.
NICE TO HAVES
- Experience with dbt for data transformations;
- Familiarity with major cloud platforms such as AWS, GCP, or Azure;
- Experience with message streaming technologies such as Apache Kafka or AWS Kinesis.
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.
Skills Required
- 4+ years of experience as a Data Engineer
- Proficiency in Python (modular, maintainable, well-tested code)
- Advanced knowledge of SQL, query optimization, and database design (normalization/denormalization)
- Hands-on experience with Snowflake
- Production experience with workflow orchestration tools (Apache Airflow, Prefect, or Dagster)
- Experience integrating with REST APIs, event-driven architectures, and building batch and streaming pipelines
- Experience implementing automated data quality checks, data lineage, and alerting mechanisms
- Experience with Git, Docker, CI/CD automation, and Infrastructure-as-Code fundamentals
- Upper-intermediate English level
- Experience with automated unit and integration testing and documentation
- Experience with dbt for data transformations
- Familiarity with major cloud platforms (AWS, GCP, or Azure)
- Experience with message streaming technologies such as Apache Kafka or AWS Kinesis
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
AgileEngine is a privately held company established in 2010 that builds dedicated teams of designers and developers. We turn good ideas into awesome software that people actually want to use. Some of the biggest names and the hottest startups around the world chose us to build their tech.
