About the Role
We are looking for an experienced Data Engineer to design, build, and optimize scalable data platforms that support analytics, reporting, machine learning, and business decision-making. You will work closely with cross-functional teams including Data Science, Product, and Engineering to deliver reliable, high-quality data solutions in a large-scale, data-driven environment.
Key Responsibilities
- Design, build, and maintain scalable data pipelines and ETL/ELT workflows.
- Develop and optimize data models, warehouse structures, and large-scale datasets for performance and efficiency.
- Partner with Data Scientists, Product Managers, and Software Engineers to understand business requirements and deliver data solutions.
- Ensure data quality through monitoring, validation, alerting, and anomaly detection processes.
- Support data governance, privacy compliance, and data lifecycle management initiatives.
- Improve reliability, scalability, and operational excellence across the data platform.
- Drive technical projects independently from requirements gathering through implementation and delivery.
Requirements
- Minimum 5 years of experience in Data Engineering, Data Platform Engineering, or a related field.
- Strong SQL expertise and experience working with large-scale data warehouses and distributed data systems.
- Proficiency in Python and/or Java for data engineering and automation.
- Hands-on experience building and maintaining production-grade ETL/ELT pipelines.
- Strong understanding of data modeling concepts, including dimensional modeling and star/snowflake schemas.
- Experience with large-scale data processing frameworks such as Spark.
- Familiarity with workflow orchestration, data quality frameworks, and monitoring tools.
- Understanding of data governance, security, and privacy best practices.
- Strong stakeholder management and communication skills.
- Ability to work independently in a fast-paced and highly collaborative environment.
Nice to Have
- Experience supporting machine learning or AI-driven data initiatives.
- Exposure to cloud-based data platforms and modern data architecture.
- Experience working with large-scale distributed systems and high-volume datasets.
What the Day-to-Day Looks Like
- Building and optimizing data pipelines that power analytics and AI initiatives.
- Collaborating with product, engineering, and data science teams on new projects.
- Troubleshooting data issues and improving data reliability.
- Designing scalable data models and warehouse solutions.
- Monitoring data quality and implementing governance best practices.
Top 3 Non-Negotiables
- Strong SQL expertise with large-scale data environments.
- Hands-on experience building production ETL/ELT pipelines using Python or Java.
- Experience with distributed data processing technologies such as Spark and modern data warehousing concepts.
Initial 8-months contract with potentiality to extend.
