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 Software Engineer to design scalable data processing systems using Spark and EMR. This person builds batch and distributed pipelines, working closely with AI and product teams to operationalize model-enabled use cases and prepare data for intelligent workflows. Strong architecture sense and comfort in data-intensive environments matter here.

WHAT YOU WILL DO

Design and develop scalable data processing solutions using Spark and EMR.
Build and maintain batch and distributed data pipelines.
Collaborate with engineering, AI, and product teams to operationalize data-driven and model-enabled use cases.
Develop software components for data transformation, feature preparation, and AI workflow integration.
Optimize pipeline performance, cost efficiency, and production reliability.
Troubleshoot data and application issues across development and production environments.
Contribute to architecture discussions, documentation, and engineering standards.
Ensure solutions align with data quality, governance, and security expectations.

MUST HAVES

4+ years of software engineering or data engineering experience.
Strong experience with Spark and distributed data processing.
Experience with Amazon EMR or similar cloud-based data processing platforms.
Proficiency in Java, Python, or related programming languages.
Exposure to AI or machine learning workflows, model integration, or data preparation for intelligent systems.
Strong understanding of scalable data architecture and performance optimization.
Strong debugging and collaboration skills.
Comfortable delivering in evolving, data-intensive environments.
Able to bridge software engineering and data engineering responsibilities.
Strong execution focus with practical architecture sense.
Upper-intermediate English level.

NICE TO HAVES

Experience with Kafka, Airflow, data lakes, or warehouse ecosystems.
Familiarity with MLOps, feature stores, or AI platform integration.
Experience with AWS-native services and observability tooling.

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

Habilidades requeridas

Apache Spark / distributed data processingAmazon EMR or cloud-based data processing platformsBatch and distributed data pipeline developmentJava or Python programmingScalable data architecture designPipeline performance and cost optimizationProduction troubleshooting and debuggingOperationalizing ML workflows / model integration (MLOps)Data transformation and feature preparationData quality, governance, and security complianceCross-functional collaboration with engineering, AI, and product teamsKafka, Airflow, data lakes, or warehouse ecosystem familiarity

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