11 of 11 Remote Permanent Parquet Jobs

Looker, etc.) Interest or experience in building internal data communities or enablement programs Working with diverse data sources (APIs, CRMs, SFTP, databases) and formats (Parquet, JSON, XML, CSV) Exposure to machine learning models or AI agents Why Join Us Help shape the future of data in an organization that More ❯

with Python. Demonstrated experience building & orchestrating automated, production-level data pipelines and solutions (ETL/ELT). Experience with file-based data storage, including Parquet or Iceberg. Experience with data catalogs (ex. Hive, AWS Glue). General understanding of key AWS services (e.g. EC2, S3, EKS, IAM, lambda). More ❯

Fabric Analytics Platform (Azure SQL, Synapse, PowerBI). • Proficient in Python for data engineering tasks, including data ingestion from APIs, creation and management of Parquet files, and execution of ML models. • Strong SQL skills, enabling support for Data Analysts with efficient and performant queries. • Skilled in optimizing data ingestion More ❯

Fabric Analytics Platform (Azure SQL, Synapse, PowerBI). • Proficient in Python for data engineering tasks, including data ingestion from APIs, creation and management of Parquet files, and execution of ML models. • Strong SQL skills, enabling support for Data Analysts with efficient and performant queries. • Skilled in optimizing data ingestion More ❯

Fabric Analytics Platform (Azure SQL, Synapse, PowerBI). • Proficient in Python for data engineering tasks, including data ingestion from APIs, creation and management of Parquet files, and execution of ML models. • Strong SQL skills, enabling support for Data Analysts with efficient and performant queries. • Skilled in optimizing data ingestion More ❯

and automation. Proficiency in building and maintaining batch and streaming ETL/ELT pipelines at scale, employing tools such as Airflow, Fivetran, Kafka, Iceberg, Parquet, Spark, Glue for developing end-to-end data orchestration leveraging on AWS services to ingest, transform and process large volumes of structured and unstructured More ❯

Good understanding of cloud environments (ideally Azure), distributed computing and optimising workflows and pipelines. Understanding of common data transformation and storage formats, e.g. Apache Parquet, Delta tables. Understanding of containerisation (e.g. Docker) and deployment (e.g. Kubernetes). Working knowledge using Spark, Databricks, Data Lakes. Follow best practices like code More ❯

e.g. duckdb, polars, daft). Familiarity with eventing technologies (Event Hubs, Kafka etc ). Deep understanding of file formats and their behaviour such as parquet, delta and iceberg. What we offer We want to give you a great work environment; contribute back to both your personal and professional development More ❯

e.g. Spark/Databricks/Delta Lake/BigQuery). Familiarity with eventing technologies (e.g. Event Hubs/Kafka) and file formats such as Parquet/Delta/Iceberg. Want to learn more? Get in touch for an informal chat. More ❯

Logic Apps, ADF, Service Bus, Functions) Comfortable working with Git , Azure DevOps , and unit testing practices Knowledge of common data formats: CSV, JSON, XML, Parquet Ability to lead integration designs with minimal rework required Preferred Qualifications Certification in SSIS or relevant Microsoft technologies Proven track record of delivering robust More ❯

Logic Apps, ADF, Service Bus, Functions) Comfortable working with Git , Azure DevOps , and unit testing practices Knowledge of common data formats: CSV, JSON, XML, Parquet Ability to lead integration designs with minimal rework required 🧾 Preferred Qualifications 🎓 Certification in SSIS or relevant Microsoft technologies 💡 Proven track record of delivering robust More ❯