Data Developer

As a Data Developer in JLLT, you will utilize AI, automation, and domain expertise to develop enterprise data solutions that drive strategic business value. You’ll translate business needs into technical requirements while demonstrating strategic awareness of how data engineering supports organizational objectives.

Working with intermediate to advanced technical skills, you’ll solve medium to high complexity data problems and collaborate with senior engineers on strategy execution. This role focuses on building production-ready data pipelines, expanding CI/CD capabilities, and delivering solutions that impact scrum team deliverables while communicating effectively with cross-functional stakeholders.

This role has flexibility to work remotely at times and candidates may be required to work outside of standard business hours on occasion to support global employees and times zones.

What your day-to-day will look like:

Advanced Data Pipeline Development

• Design and implement complete ETL/ELT workflows using intermediate to advanced techniques
• Build and modify CI/CD pipelines for data processing workflows
• Develop native data ingestion capabilities from various sources (APIs, databases, file systems)
• Implement data validation, error handling, and monitoring in production pipelines

• Incorporate AI and automation patterns into data engineering solutions
• Develop solutions that leverage automation for improved efficiency and scalability
• Apply intermediate Python techniques including decorators, generators, and design patterns
• Build reusable components and frameworks for team use

• Translate business requirements into technical data engineering solutions
• Collaborate with product managers, analysts, and other stakeholders on data needs
• Participate actively in scrum/agile development processes
• Provide technical expertise to support strategic decision-making

• Apply data modeling principles and data warehousing concepts
• Design database schemas and data integration patterns
• Work with cloud services (Azure/AWS/GCP) for scalable data solutions
• Optimize data storage and retrieval for performance and cost

Experience & Education

• Bachelor’s degree in Computer Science, Information Systems, Mathematics, Statistics, or related quantitative discipline
• 3+ years of experience in data engineering, data development, or related technical field
• Proven experience building ETL/data pipelines in production environments
• Experience with agile development methodologies and cross-functional teams

• Programming: Intermediate Python skills including decorators, generators, object-oriented programming
• SQL: Solid SQL proficiency with query optimization and performance tuning experience
• Data Engineering: Experience with data orchestration platforms (Airflow, Azure Data Factory, SSIS, or similar)
• Big Data: Familiarity with Apache Spark, PySpark, or similar distributed processing frameworks
• Cloud Platforms: Hands-on experience with Azure, AWS, or GCP data services (Databricks, Azure Functions, Delta Lake, etc.)
• Data APIs & Semantic Layer: Familiarity with semantic layer tools (CubeJS or similar) for data access and analytics
• CI/CD: Understanding of continuous integration/deployment for data pipelines
• Design Patterns: Knowledge of software design patterns and their application in data engineering
• AI/Automation: Basic understanding of AI/automation tools and their integration into data workflows

• Technical Skills (40%): Built ETL/data pipelines, production experience, CI/CD knowledge, AI/automation awareness
• Problem-Solving (25%): Production pipeline experience, architecture basics, scalability awareness
• Communication (20%): Agile team experience, stakeholder communication, cross-functional work
• Learning & Growth (15%): AI/automation project exposure, learning track record, business understanding