Full Stack Data Engineer

We are seeking a Full Stack Data Engineer to own our client's data platform end-to-end, encompassing ingestion, pipeline development, API creation, and enabling self-serve analytics. This role involves working across the entire data lifecycle, requiring close collaboration with Product, Engineering, and other stakeholders to design, build, and maintain robust data solutions. You will be instrumental in transforming raw data into actionable insights, ensuring data quality, scalability, and accessibility for our clients.

About the Role

You will lead the end-to-end development and optimization of our data infrastructure, ensuring seamless data flow from source to consumption. This includes designing and implementing scalable ingestion pipelines, building efficient data processing workflows, developing and maintaining APIs for data access, and creating self-service analytics capabilities. Your work will directly impact how our clients leverage their data, requiring a blend of technical expertise and collaborative problem-solving.

Key Responsibilities

• Design, develop, and maintain scalable data ingestion pipelines and ETL/ELT processes.
• Build and optimize data processing workflows and data warehousing solutions.
• Develop, document, and maintain robust APIs for data access and integration.
• Implement and manage self-serve analytics platforms and dashboards.
• Collaborate with Product, Engineering, and data consumers to define requirements and deliver solutions.
• Ensure data quality, governance, and security throughout the data lifecycle.
• Optimize data storage, processing, and retrieval for performance and cost-efficiency.

Requirements

• Proven experience as a Full Stack Data Engineer or similar role.
• Strong proficiency in SQL and experience with data modeling and database design.
• Experience with Python and/or Java for data processing and scripting.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and big data technologies (e.g., Spark, Hadoop).
• Experience building and deploying data APIs and web services.
• Understanding of data warehousing concepts and data lake architectures.
• Ability to collaborate effectively within cross-functional teams.
• Strong problem-solving skills and attention to detail.