1 to 25 of 49 Parquet Jobs in London

dashboards (data validation, extract refresh checks, reconciliation to source). Nice-to-Have Experience with tools such as PySpark, Spark SQL, Hive, Impala, HDFS, Parquet, and Oracle databases. Exposure to data governance concepts: critical data elements (CDEs), lineage, data quality dimensions, audit frameworks. Experience running delivery (intake, triage, prioritization ...

dashboards (data validation, extract refresh checks, reconciliation to source). Nice-to-Have Experience with tools such as PySpark, Spark SQL, Hive, Impala, HDFS, Parquet, and Oracle databases. Hands-on exposure to DCRM tooling and operational exception management processes. Experience with governance/catalog tools and lineage documentation methods ...

Python for data engineering and automation. Hands‐on experience with PySpark and Spark SQL in production environments. Solid knowledge of Hive, Impala, HDFS, and Parquet . Advanced SQL skills; experience with Oracle databases . Experience designing and supporting ETL/ELT pipelines and data quality frameworks . Working knowledge ...

environment. Experience working with distributed data processing frameworks such as Apache Spark . Working knowledge of common data formats such as JSON , Avro and Parquet . For More Experienced Candidates Stronger ownership of technical design across multiple datasets or pipeline domains. Experience guiding implementation standards, code quality and engineering ...

data warehousing (Redshift, dimensional modeling) Proficiency in Python or Scala for data engineering Experience with S3-based data lake architecture (partitioning, cataloging, formats like Parquet) Experience migrating data pipelines from on-prem or other cloud platforms Understanding of data governance, security, and access control on AWS Experience with ...

based environment Advanced experience working and understanding the tradeoffs of at least one of the following Data Lake table/file formats: Delta Lake, Parquet, Iceberg, Hudi Experience working with lakehouse/medallion architectures in Databricks Experience with experimentation support tooling (such as Optimizely) A genuine curiosity about ...

environment. Experience working with distributed data processing frameworks such as Apache Spark . Working knowledge of common data formats such as JSON , Avro and Parquet . Technology Environment The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise ...

environment. Experience working with distributed data processing frameworks such as Apache Spark . Working knowledge of common data formats such as JSON , Avro and Parquet . Technology Environment The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise ...

required• Event streaming or real-time processing with Kafka, Kinesis, Flink, Spark Structured Streaming, or similar technologies.• Distributed processing with Spark and familiarity with Parquet, Avro, JSON, and open table formats.• Search or retrieval systems such as Elasticsearch/OpenSearch, vector databases, or embedding pipelines.• Feature stores, ML data ...

Automation Python and SQL PostgreSQL and Amazon RDS Power Automate Power BI REST API and enterprise integration architecture JSON, XML, XSD, CSV, and Parquet OCR and unstructured-document processing Data modeling and metadata management IAM, role-based security, and secrets management Git, CI/CD, version control, and deployment ...

production data pipelines in a collaborative engineering environment Experience with distributed data processing frameworks such as Apache Spark Working knowledge of JSON, Avro and Parquet Nice to have: technical design ownership across multiple datasets or pipeline domains, experience guiding implementation standards and engineering practices, ability to lead delivery ...

invalidation, persistence strategy, data consistency MongoDB TimescaleDB NATS JetStream AWS S3/Glue Data lake staging, archival, batch ingestion into Snowflake Partitioning, file format (Parquet/ORC), Lake Formation governance Finance Domain Knowledge Candidates should have hands‐on data architecture experience in one or more of the following financial ...

building lean processes Experience with distributed data processing Experience with monitoring, testing, and data quality Experience building robust pipelines from diverse sources e.g. parquet, SQL & no-SQL databases, API endpoints It would be helpful to have experience/expertise/knowledge in the following: Python AWS Kubernetes Spark & distributed ...

building lean processes Experience with distributed data processing Experience with monitoring, testing, and data quality Experience building robust pipelines from diverse sources e.g. parquet, SQL & no-SQL databases, API endpoints It would be helpful to have experience/expertise/knowledge in the following: Python AWS Kubernetes Spark & distributed ...

Role Description The Technical Analyst – Data Lineage will support a Data Governance, Controls, and Reporting program for a top-tier banking client. Responsible for establishing and validating end-to-end lineage across critical datasets used ...

Orchestra for task orchestration Terraform for infrastructure Lightdash for data applications Airflow and Astronomer for job scheduling and tracking Circle CI for continuous deployment Parquet and Delta file formats on S3 for data lake storage Spark for data processing SparkSQL for analytics Why else you'll love it here ...

Modern Tech Stack: Experience is helpful, but not essential: Languages: Python, SQL, Terragrunt, JavaScript Cloud: AWS (primary), some GCP Warehouse & Storage: Snowflake, S3/Parquet Data & ETL: dbt, Fivetran Platform & Infra: Kubernetes, Kafka, RabbitMQ, Argo, GitHub Actions, HashiCorp Vault Observability: Datadog, Grafana Dashboarding: Preset Other: Claude WHAT ...

modern data stack, building data ingestion pipelines and working with ETL and orchestration tools (e.g., Airflow, Luigi, Argo, dbt), big data technologies (Spark, Kafka, Parquet), and web frameworks for model serving (e.g. Flask or FastAPI). Data Science: Familiarity or experience with classical NLP techniques (BERT, topic modelling, summarisation ...

/SQL for data modelling and analytics Streamlit for data applications and visualisations Airflow for job scheduling and tracking CircleCI for continuous deployment Parquet and Delta file formats on S3 for data lake storage Terraform for our infrastructure definition Kubernetes for data services and task orchestration Datadog/Grafana ...

experience with Apache Spark and Apache Flink. Strong understanding of Apache HTTP, Envoy, and REST API design. Experience working with Protobuf, Avro, and Parquet data formats. Knowledge of Iceberg, Databricks, and Hadoop ecosystems. Skills that will help Follows TDD, ATDD and Clean Coding practices and used to setting ...

building lean processes Experience with distributed data processing Experience with monitoring, testing, and data quality Experience building robust pipelines from diverse sources e.g. parquet, SQL & no-SQL databases, API endpoints It would be helpful to have experience/expertise/knowledge in the following: Python AWS Spark & distributed computing ...

evolve the platform. Experience is helpful, but not essential:* **Languages:** Python, SQL, Terragrunt, JavaScript* **Cloud:** AWS (primary), some GCP* **Warehouse & Storage:** Snowflake, S3/Parquet* **Data & ETL:** dbt, Fivetran* **Platform & Infra:** Kubernetes, Kafka, RabbitMQ, Argo, GitHub Actions, HashiCorp Vault* **Observability:** Datadog, Grafana* **Dashboarding:** Preset* **Other**: Claude### **What ...

modern data stack, building data ingestion pipelines and working with ETL and orchestration tools (e.g., Airflow, Luigi, Argo, dbt), big data technologies (Spark, Kafka, Parquet), and web frameworks for model serving (e.g. Flask or FastAPI). Data Science: Familiarity or experience with classical NLP techniques (BERT, topic modelling, summarisation ...

these capabilities responsibly. Modern Data Platform Expertise You're familiar with contemporary data platforms and tools, including data lakes, open table formats such as Parquet and Iceberg, ETL and ELT pipelines, multiple query engines, and BI tools such as Power BI. You're comfortable working across cloud environments including ...

definition Kubernetes for data services and task orchestration Argo CD for application deployments Airflow purely for job scheduling and tracking CircleCI for continuous deployment Parquet and Delta file formats on S3 for data lake storage Postgres/Aurora for our relational databases Spark for data processing dbt for data ...