Sr. Data Architect

DexCare is looking for a Senior Data Engineer to join the team! The Senior Data Engineer will report directly to the VP of Data Science and be responsible for the development of DexCare's data services that support data dashboards and intelligent services.

Responsibilities:

• Design, develop, and implement end-to-end data pipelines to support data collection, processing, and transformation from various sources into usable formats.
• Lead the architecture and development of data solutions that are scalable, efficient, and maintainable, ensuring high-quality code, documentation, and adherence to best practices.
• Optimise data pipelines for performance, reliability, and scalability, and troubleshoot issues as they arise in collaboration with the operations team.
• Collaborate with data scientists and analysts to understand their data requirements, provide clean and accessible data, and assist in building data models and algorithms.
• Work closely with cross-functional teams to gather and refine data requirements, ensuring data integrity and accuracy throughout the entire data lifecycle.
• Stay up to date with the latest technologies, trends, and best practices in data engineering and analytics, and recommend relevant tools and technologies to enhance the company's data capabilities.
• Mentor and provide technical guidance to junior members of the data engineering team, fostering skill development and growth.
• Participate in code reviews and design discussions and contribute to improving the overall data engineering processes and practices within the organisation.
• Participate in on-call rotation.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience (6-7+ years) working as a data engineer, with a focus on designing and implementing data pipelines, ETL processes, and data warehousing solutions.
• Strong programming skills in languages like Python, Java, Scala, or similar, with experience in using data engineering frameworks and libraries.
• Expertise in working with relational databases (e. g., PostgreSQL, MySQL) and NoSQL databases (e. g., MongoDB, Cassandra).
• Hands-on experience with distributed data processing frameworks such as Apache Spark, Hadoop, or similar technologies.
• Proficiency in data modelling, data architecture, and schema design for efficient storage and retrieval.
• Experience with cloud platforms like AWS, Azure, or GCP and familiarity with services like AWS Glue, Azure Data Factory, DBT, or Google Dataflow.
• Solid understanding of data security, privacy, and compliance considerations in data engineering.
• Excellent problem-solving skills and the ability to troubleshoot complex data-related issues.
• Strong communication skills and the ability to collaborate effectively with cross-functional teams.
• Prior experience mentoring junior team members and leading technical initiatives is a plus.