Principal Data Engineer

🔥 8 minutes ago

🇵🇱 Poland – Remote

⏰ Full Time

🔴 Lead

🚰 Data Engineer

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Simple Machines

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

💼 Consulting

Artificial Intelligence • Consulting

Simple Machines is an Australian based firm of expert consultants at the intersection of data architecture, data engineering, data science and software application development. They specialize in architecting and engineering highly performant, distributed, data driven platforms and machine learning applications that perform at massive scale. Simple Machines partners with enterprises, governments, and global technology companies to put their data to work in the real world. The company is a Preferred Confluent consulting and training partner, offering specialist consulting services in Kafka, and is also partnered with Databricks and Lightbend, providing training and consulting services in Spark and Scala.

📋 Description

• Own the end-to-end architecture of modern, cloud-native data platforms • Design scalable data ecosystems using data mesh, data products, and data contracts • Make architectural decisions across ingestion, storage, processing, and access layers • Ensure platforms are secure, compliant, and production-grade • Design and deliver cloud-native data platforms using Databricks, Snowflake, AWS, and GCP • Integrate with client systems to enable scalable, consumer-oriented data access • Build and optimise batch and real-time pipelines • Work with Kafka, Flink, Kinesis, and Pub/Sub • Orchestrate workflows using Airflow, Dataflow, and Glue • Process and transform large datasets using Spark and Flink • Work across relational, NoSQL, and analytical stores including Postgres, BigQuery, Snowflake, Cassandra, and MongoDB • Optimise storage formats and access patterns including Parquet, Delta, ORC, and Avro • Implement secure, compliant data solutions with security by design • Embed data governance while maintaining developer velocity • Work directly with clients to understand problems and shape solutions • Translate business needs into pragmatic engineering decisions • Act as a trusted technical advisor • Set engineering standards, patterns, and best practices • Review designs and code, providing technical direction and mentorship • Improve data quality, testing, observability, and operational excellence

🎯 Requirements

• Strong Python and SQL • Deep experience with Spark and modern data platforms (Databricks / Snowflake) • Solid grasp of cloud data services (AWS or GCP) • Demonstrated ownership of large-scale data platform architectures • Strong data modelling skills and architectural decision-making ability • Ability to balance trade-offs between performance, cost, and complexity • Experience building and operating large-scale data pipelines in production • Experience with multiple storage technologies and formats • Infrastructure-as-code experience with Terraform or Pulumi • CI/CD pipeline experience using tools such as GitHub Actions or ArgoCD • Experience with data testing and quality frameworks such as dbt, Great Expectations, or Soda • Experience in consulting or professional services environments • Ability to challenge assumptions and guide clients toward better outcomes • Comfortable mentoring senior engineers and influencing technical culture

🏖️ Benefits

• Interesting, high-impact problems • Opportunity to build modern platforms rather than maintain legacy systems • Work alongside senior engineers • Autonomy and influence • Room to grow