Senior Data Engineer - Part-Time

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

1. Strong SQL expertise with large-scale data environments.
2. Hands-on experience building production ETL/ELT pipelines using Python or Java.
3. Experience with distributed data processing technologies such as Spark and modern data warehousing concepts.

Initial 8-months contract with potentiality to extend.