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
- Data Pipeline Development: Design, build, and maintain reliable, scalable ETL/ELT workflows that process batch and streaming data from diverse sources.
- Data Warehousing & Modeling: Design efficient, production-ready schemas (normalized and denormalized) in Snowflake to optimize query performance and enable enterprise analytics.
- API & Event Integration: Connect and ingest data from third-party REST APIs, event-driven streams, and batch sources into core data storage platforms.
- Orchestration: Maintain and expand workflow orchestration pipelines using modern tools (Airflow, Prefect, or Dagster).
- Data Quality & Observability: Implement automated testing, validation, lineage tracking, and proactive alerting frameworks to guarantee data accuracy and system uptime.
- DataOps & Engineering Standards: Drive CI/CD best practices, maintain code bases using Git and Docker, and adopt basic Infrastructure-as-Code (IaC) patterns.
- Code Excellence: Apply modern software engineering standards—including design patterns, automated unit/integration testing, and clear documentation—to data repositories.
MUST HAVES
-
4+ years of experience as a Data Engineer
.
-
Core Python Fundamentals
: Demonstrable expertise writing modular, maintainable, and well-tested Python code (OOP/functional patterns, package management, standard testing frameworks).
-
Advanced SQL & Modeling
: Deep knowledge of complex SQL queries, query optimization, database design principles, and normalization/denormalization patterns.
-
Data Warehousing
: Solid, hands-on experience building, managing, and optimizing data architectures within Snowflake.
-
Workflow Orchestration
: Production experience using workflow orchestration engines like Apache Airflow, Prefect, or Dagster.
-
Integrations & Ingestion
: Hands-on experience working with REST APIs, event-driven architectures, and both batch and streaming pipelines.
-
Data Quality & Lineage
: Experience building automated data quality checks, data lineage, and alerting mechanisms (e.g., using tools like dbt test, Great Expectations, or similar).
-
DevOps / DataOps Practices
: Strong skills in version control (Git), containerization (Docker), CI/CD automation, and familiarity with Infrastructure-as-Code basics.
- Upper-intermediate English level.
NICE TO HAVES
- Experience with dbt (data build tool) for data transformations.
- Familiarity with major cloud providers (AWS, GCP, or Azure).
- Exposure to message streaming tech like Apache Kafka or AWS Kinesis.
PERKS AND BENEFITS
-
Growth without limits
: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
-
Competitive compensation
: get recognition that reflects your skills and impact, with regular performance and compensation reviews
-
Flexibility
: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
-
Meaningful, modern projects
: build impactful products using modern technologies alongside global teams and leading brands
-
Collaborative culture
: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
-
Well-being & support
: access local well-being programs and people-focused support tailored to your location
