Senior/Principal/Associate Director

Overview Senior/Principal/Associate Director - Data Engineering - Multiple Levels at Simple Machines.
Simple Machines is a leading independent boutique technology firm with a global presence, including teams in London, Sydney, San Francisco, and New Zealand.
We specialise in technology solutions at the intersection of data, AI, machine learning, data engineering, and software engineering.
Our mission is to help enterprises, technology companies, and governments better connect with and understand their organisations, their people, their customers, and citizens.
We are a team of engineers and technologists dedicated to unleashing the potential of data in new and impactful ways.
We design and build bespoke data platforms and unique software products, create and deploy intelligent systems, and bring engineering expertise to life by transforming data into actionable insights and tangible outcomes.Technical Responsibilities Developing Data Solutions : Implement and enhance data-driven solutions integrating with clients' systems using state-of-the-art tools such as Databricks, Snowflake, Google Cloud, and AWS.
Embrace modern data architecture philosophies including data products, data contracts, and data mesh to ensure a decentralized and consumer-oriented approach to data managementData Pipeline Development : Develop and optimise high-performance, batch and real-time data pipelines employing advanced streaming technologies like Kafka, and Flink.
Utilise workflow orchestration tools such as Dataflow and AirflowDatabase and Storage Optimization : Optimize and manage a broad array of database technologies, from traditional relational databases (e.g., PostgreSQL, MySQL) to modern NoSQL solutions (e.g., MongoDB, Cassandra).
Focus on strategies that enhance data accessibility, integrity, and performanceBig Data Processing & Analytics : Utilise big data frameworks such as Apache Spark and Apache Flink to address challenges associated with large-scale data processing and analysis.
These technologies are crucial for managing vast datasets and performing complex data transformations and aggregationsCloud Data Management : Implement and oversee cloud-specific data services including AWS Redshift, S3, Google BigQuery, and Google Cloud Storage.
Leverage cloud architectures to improve data sharing and interoperability across different business unitsSecurity and Compliance : Ensure all data practices comply with security policies and regulations, embedding security by design in the data infrastructure.
Incorporate tools and methodologies recommended for data security and compliance, ensuring robust protection and governance of data assetsConsulting Responsibilities Client Advisory : Provide expert advice to clients on optimal data practices that align with their business requirements and project goalsTraining and Empowerment : Educate client teams on the latest technologies and data management strategies, enabling them to efficiently utilise and maintain the solutions we have developedProfessional Development : Keep up with the latest industry trends and technological advancements, continually upgrading skills and achieving certifications in the technologies Simple Machines implements across its client baseIdeal Skills and Experience Core Data Engineering Tools & Technologies : Demonstrates proficiency in SQL and Spark, and familiarity with platforms such as Databricks and Snowflake.
Well-versed in various storage technologies including AWS S3, Google Cloud BigQuery, Cassandra, MongoDB, Neo4J, and HDFS.
Adept in pipeline orchestration tools like AWS Glue, Apache Airflow, and dbt, as well as streaming technologies like Kafka, AWS Kinesis, Google Cloud Pub/Sub, and Azure Event HubsData Storage Expertise : Knowledgeable in data warehousing technologies like BigQuery, Snowflake, and Databricks, proficient in managing various data storage formats including Parquet, Delta, ORC, Avro, and JSON to optimise data storage and retrievalBuilding and Managing Large-scale Data Systems : Experienced in developing and overseeing large-scale data pipelines and data-intensive applications within production environmentsData Modelling Expertise : Proficient in data modelling, understanding the implications and trade-offs of various methodologies and approachesInfrastructure Configuration for Data Systems : Competent in setting up data system infrastructures, favouring infrastructure-as-code practices using tools such as Terraform and PulumiProgramming Languages : Proficient in Python and SQL, with additional experience in programming languages like Java, Scala, GoLang, and Rust considered advantageousCI/CD Implementation : Knowledgeable about continuous integration and continuous deployment practices using tools like GitHub Actions and ArgoCD, enhancing software development and quality assuranceTesting Tools and Frameworks : Experienced with data quality and testing frameworks such as DBT, Great Expectations, and Soda, ensuring the reliability of complex data systemsCommercial Application of Data Engineering Expertise : Demonstrated experience in applying data engineering skills across various industries and organisations in a commercial contextAgile Delivery and Project Management : Skilled in agile, scrum, and kanban project delivery methods, ensuring efficient and effective solution developmentConsulting and Advisory Skills : Experienced in a consultancy or professional services setting, offering expert advice and crafting customised solutions that address client needs.
Effective in engaging stakeholders and translating business requirements into practical data engineering strategiesJob Details Seniority level : Mid-Senior levelEmployment type : Full-timeJob function : Engineering and Information TechnologyIndustries : Non-profit Organizations and Primary and Secondary Education#J-18808-Ljbffr