> Markdown version of [/jobs/ext/4699857-data-ingestion-engineer](https://www.wearedevelopers.com/jobs/ext/4699857-data-ingestion-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Ingestion Engineer - **Company:** Focus Cloud Limited - **Location:** London, United Kingdom - **Experience:** Expert - **Salary:** £169,000 - £182,000 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Apache HTTP Server, Computer Vision, Microsoft Azure, Big Data, Databases, Continuous Integration, Data Dictionary, Database Queries, Python (Programming Language), Performance Tuning, Standard Sql, Workflow Management Systems, Parquet, Data Processing, Google Cloud, Cloud Platform System, Data Ingestion, Sql Optimization, Apache Spark, Git, Data Lakes, Pyspark, Data Lineage, Apache Kafka, Spark Streaming, Video Streaming, Lidar, Software Version Control, Data Pipelines, Databricks - **Published:** November 13, 2026 - **Apply:** https://www.careerboard.com/gb/en/find-jobs-in-United-Kingdom/-F455E699E309042D50/ ## About the Role * Proven commercial experience as a Data Engineer or Data Ingestion Engineer * Strong Python programming for data processing and pipeline development * Hands-on PySpark experience with large distributed datasets * Advanced SQL, including complex queries, performance tuning and data modelling * Track record of working with large-scale data, from gigabytes up to multiple terabytes * Good understanding of data domains: how data is produced, what it represents and how it should be structured * Experience with data quality, validation and schema evolution * Familiarity with a cloud data platform such as AWS, Azure, GCP or Databricks * Version control (Git) and CI/CD for data pipelines Desirable Experience * Automotive sector experience, such as vehicle, connected-car, telematics or autonomous driving data * Working knowledge of IMU (inertial measurement unit) data or other high-frequency sensor and time-series data * Exposure to computer vision or robotics datasets, such as camera, lidar or sensor-fusion data * Financial services experience, particularly with large, regulated or high-volume datasets * Streaming technologies such as Kafka or Spark Structured Streaming * Lakehouse formats and tooling such as Delta Lake, Apache Iceberg or Parquet * Orchestration tools such as Airflow or Dagster ## Description * Design, build and maintain batch and streaming ingestion pipelines using Python, PySpark and SQL * Ingest structured, semi-structured and sensor or time-series data from files, APIs, databases and device feeds * Process and transform datasets from gigabytes to multiple terabytes efficiently and cost-effectively * Understand the business and technical meaning of each data domain, and model data so it is usable downstream * Build data quality checks, validation, schema management and monitoring into every pipeline * Tune Spark jobs for performance, partitioning and storage layout at scale * Work with data scientists, ML engineers and analysts to understand their needs and deliver the right datasets * Document pipelines, data lineage and data dictionaries * Support production pipelines, troubleshoot failures and improve reliability