We are looking for a hands-on Data Engineer who is passionate about solving business problems through innovation and engineering practices. As a Data Engineer, you will leverage your deep technical knowledge to drive the creation of high-quality software products. You will also be expected to mentor other engineers, share your technical expertise, and promote a culture of technical excellence within the team. The Data Engineer will report to an Engineering Manager. There is an expectation to contribute to the codebase and deliver solutions against the sprint-level commitments.
Responsibilities
- · Code contributing member of multiple Agile teams, working to deliver sprint goals.
- · Demonstrating deep technical knowledge and expertise in software development, including programming languages, frameworks, and best practices. Providing guidance and mentorship to junior team members.
- · Actively contributes to the implementation of critical features and complex technical solutions. Write clean, efficient, and maintainable code that meets the highest standards of quality.
- · Collaborate with other Engineers to define and evolve the overall system architecture and design.
- · Provide guidance on scalable, robust, and efficient solutions that align with business requirements and industry best practices.
- · Offer expert engineering guidance and support to multiple teams, helping them overcome technical challenges, make informed decisions, and deliver high-quality software solutions. Foster a culture of technical excellence and continuous improvement.
- · Stay up to date with emerging technologies, tools, and industry trends. Evaluate their potential impact on the organization and provide recommendations for technology adoption and innovation.
Required Qualifications
- · 4+ years’ experience of implementing data-intensive solutions using agile methodologies.
- · Proficient in one or more programming languages commonly used in data engineering such as Python, Java, or Scala.
- · Multiple years of experience with software engineering best practices (unit testing, automation, design patterns, peer review, etc.)
- · Strong proficiency in working with relational databases and using SQL for data querying, transformation, and manipulation.
- · Clear understanding of Data Structures and Object Oriented Principles.
- · Experience of modelling data for analytical consumers
- · Ability to automate and streamline the build, test and deployment of data pipelines.
- · Experience with Hadoop for data storage and processing is valuable, as is exposure to modern data platforms such as Snowflake and Databricks.
- · Multiple years of experience architecting and building horizontally scalable, highly available, highly resilient, and low latency applications
- · Multiple years of experience with Cloud-native development and Container Orchestration tools (Serverless, Docker, Kubernetes, OpenShift, etc.).
- · Proven experience of providing technical vision and guidance to a data team.
- · Thrives in a dynamic environment, capable of managing multiple tasks simultaneously while maintaining a high standard of work.
- · BA/BS degree or equivalent work experience.
Preferred Qualifications
· Familiarity with open-source data engineering tools and frameworks (e.g. Spark, Kafka, Beam, Flink, Trino, Airflow, DBT) is a valuable asset
· Exposure to a range of table and file formats including Iceberg, Hive, Avro, Parquet and JSON
· Experience in cloud native technologies and patterns (AWS, Google Cloud)
· Exposure to Infrastructure as Code tools (i.e., Terraform, Cloudformation, etc.)
· Experience of driving and/or influencing the data strategy of your team or organization
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Job Family Group:
Technology
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Job Family:
Digital Software Engineering
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Time Type:
Full time
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