Architect

Summary

Join Datacom's growing analytics team as a Databricks Architect, working on diverse customer projects focused on data. Collaborate with developers, data scientists, and engineers to design and maintain data architectures enabling data-driven insights. Translate business requirements into scalable data solutions, showcasing expertise in Databricks architecture and the platform. This role offers flexibility with a location of your choice. Datacom provides a dynamic and supportive work environment with various perks. The successful candidate will have a passion for Databricks and a proven track record in data solutions development.

Requirements

• Extensive knowledge of Databricks architecture and features
• Experience in the design, development and implementation of data solutions using Databricks
• Experience in data ingestion tools such as Apache Kafka, Informatica, AWS Glue, Azure event hubs and Fivetran
• Strong programming skills, especially Python, Java, Scala, C++, C# etc
• Cloud platforms such as Azure, AWS & GCP
• Relational database management systems such as SQL Server, Redshift etc
• Distributed processing technologies such as Apache Spark
• Working knowledge of message queuing, stream processing, and highly scalable data stores
• Experience building CI/CD Pipelines such as GITHUB, Azure DevOps, etc
• Degree in Computer Science, Data Science, Statistics or related field
• Ability to connect to customer’s specific business problems and Databricks solutions
• Minimum 3+ years’ experience in Databricks development
• Experience developing and deploying data pipelines into live environments
• A passion for lean, clean and maintainable code
• Strong analytic skills related to working with datasets, both structured and unstructured
• Curious and enthusiastic mindset
• The desire to grow and to share insights with others

Responsibilities

• Design data platforms, distributed systems, data lakes & data stores
• Creating software solutions for data ingest & integration
• Developing and operationalising reliable data pipelines & ETL patterns
• Building analytics tools to provide actionable insights and solve business problems
• Infrastructure development
• Wrangling and integrating data from multiple sources
• Identifying ways to improve data reliability, efficiency and quality

Preferred Qualifications

• The desire to grow and to share insights with others
• Machine Learning frameworks and theory
• Analytic platforms & tools such as Databricks, Alteryx, SAS, KNIME or Datarobot
• Data vault / Kimball modelling methodology
• DevOps / DataOps

Benefits

• Remote working
• Flexi-hours
• Professional development courses