Principal / Senior Data Engineer (Data Platforms)

OverviewPrincipal / Senior Data Engineer (Data Platforms) – Christchurch, New ZealandSimple Machines is a leading independent boutique technology firm with a global presence.

We specialise in technology solutions at the intersection of data, AI, machine learning, data engineering, and software engineering.

We design and build bespoke data platforms and software products, create and deploy intelligent systems, and transform data into actionable insights and tangible outcomes.ResponsibilitiesTechnical ResponsibilitiesDeveloping Data Solutions : Implement and enhance data-driven solutions interfacing with clients\' systems using tools such as Databricks, Snowflake, Google Cloud, and AWS.

Apply data products, data contracts, and data mesh concepts to enable decentralized, consumer-oriented data management.Data Pipeline Development : Build and optimise high-performance batch and real-time data pipelines using Kafka and Flink; utilise workflow orchestration tools like Dataflow and Airflow.Big Data Processing & Analytics : Use Apache Spark and Apache Flink for large-scale data processing, transformations, and analytics.Cloud Data Management : Manage cloud data services (AWS Redshift, S3; Google BigQuery, Google Cloud Storage) to improve data sharing and interoperability across business units.Security and Compliance : Ensure data practices comply with security policies and regulations; embed security by design in data infrastructure.Consulting ResponsibilitiesClient Advisory : Provide expert advice on data practices aligned with client goals and project needs.Professional Development, Training & Empowerment : Stay current with industry trends, upgrade skills, and educate client teams to enable sustainable use of solutions.Ideal Skills and ExperienceCore Data Engineering Tools & Technologies : Proficiency in SQL and Spark; familiarity with Databricks and Snowflake; experience with AWS S3, Google Cloud BigQuery; knowledge of Cassandra, MongoDB, Neo4J, and HDFS.

Proficiency with pipeline orchestration (AWS Glue, Apache Airflow, DBT) and streaming (Kafka, AWS Kinesis, Google Cloud Pub / Sub, Azure Event Hubs).

Data Storage Expertise : Experience with data warehousing (BigQuery, Snowflake, Databricks) and storage formats (Parquet, Delta, ORC, Avro, JSON).

Data Modelling : Proficient in data modelling and evaluating trade-offs across methodologies.Infrastructure Configuration : Infrastructure-as-code with Terraform and Pulumi.Programming Languages : Python and SQL; Java, Scala, GoLang, Rust are advantageous.CI / CD : Knowledge of GitHub Actions and ArgoCD for CI / CD.Agile Delivery : Experience with agile, scrum, and kanban.Consulting & Advisory Skills : Experience in consultancy or professional services; ability to translate business requirements into data engineering solutions.Professional Experience and QualificationsExperience : At least 8+ years of data engineering or equivalent in commercial, enterprise, or startup environments.

Consulting experience is beneficial.Education : Degree or equivalent in computer science or related field.Right to Work : Must have full New Zealand working rights and reside in Christchurch.BenefitsIn Christchurch, the office is a thoughtfully renovated former print-house on StAsaph Street, award-winning and reflecting a commitment to a high-quality, creative work environment.

The team includes expert consultants, data architects, and senior engineers delivering real-time pipelines and data mesh solutions using tools like Databricks, Snowflake, GCP, AWS, Kafka, Flink, and dbt.Location and LogisticsChristchurch, Canterbury, New ZealandSeniority levelMid-Senior levelEmployment typeFull-timeJob functionData EngineeringIndustriesNon-profit Organizations and Primary and Secondary Education

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