Jobs and Careers

Data Engineer (Middle) ID43228

Fort Lauderdale, United Statesfull_timeVerifiedPosted 1 Dec 2025

About the role

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 Middle/Senior Data Engineer , you’ll help build a high-impact Thematic Research Platform that processes large-scale financial data and powers daily insights for researchers and data scientists. You’ll design and optimize ETL pipelines, develop cloud data warehousing solutions, and shape AWS-based infrastructure using tools like Airflow, Spark, and Terraform. This role offers the chance to work on complex data ecosystems, drive performance improvements, and collaborate closely with cross-functional teams in a technically rich, mission-driven environment. WHAT YOU WILL DO

Build and support ETL pipelines;
Monitor data pipelines, identify bottlenecks, optimize data processing and storage for performance and cost-effectiveness;
Collaborate effectively with cross-functional teams including data scientists, analysts, software engineers, and business stakeholders;
Work with Terraform to build AWS infrastructure;
Analyze sources and build Cloud Data Warehouse and Data Lake solutions.

MUST HAVES

3+ years of experience with Python ;
3+ years of experience in a Data Engineering role;
Proficiency in programming languages commonly used in data engineering such as Python, SQL, and optionally Scala for working with data processing frameworks like Spark and libraries like Pandas;
Proficiency in designing, deploying, and managing data pipelines using Apache Airflow for workflow orchestration and scheduling;
Ability to design, develop, and optimize ETL processes to move and transform data from various sources into the data warehouse, ensuring data quality, reliability, and efficiency;
Knowledge of big data technologies and frameworks such as Apache Spark for processing large volumes of data efficiently;
Extensive hands-on experience with various AWS services relevant to data engineering, including Amazon MWAA, Amazon S3, Amazon RDS, Amazon EMR, AWS Lambda, AWS Glue, Amazon Redshift, AWS Data Pipeline, Amazon DynamoDB;
Deep understanding and practical experience in building and optimizing cloud data warehousing solutions;
Ability to monitor data pipelines, identify bottlenecks, and optimize data processing and storage for performance and cost-effectiveness;
Excellent communication skills to collaborate effectively with cross-functional teams;
Bachelor’s degree in computer science/engineering or other technical field, or equivalent experience;
Upper-intermediate English level.

NICE TO HAVES

Familiarity with the fintech industry, understanding of financial data, regulatory requirements, and business processes specific to the domain;
Documentation skills to document data pipelines, architecture designs, and best practices for knowledge sharing and future reference;
Experience with GCP services relevant to data engineering;
Experience with Snowflake;
Experience with OpenSearch or Elasticsearch;
Experience using Jupyter for data analysis;
Experience with Bitbucket and Bamboo;
Experience with Terraform.

PERKS AND BENEFITS

Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happies