1 to 25 of 52 Hadoop Jobs in the Midlands

Strong communication skills and adaptability in dynamic environments. Nice-to-Have Requirements: Experience in designing scalable data solutions. Knowledge of big data technologies like Hadoop, Kafka, or Spark. Experience with data visualization tools such as Tableau or Power BI. Hands-on experience with data warehousing solutions like Snowflake or More ❯

Several years of experience in data engineering or a related field, with expertise in designing scalable data solutions. Familiarity with big data technologies like Hadoop, Kafka, or Spark for processing large-scale data. Experience with data visualization tools such as Tableau, Power BI, or similar platforms for building reports More ❯

Several years of experience in data engineering or a related field, with expertise in designing scalable data solutions. Familiarity with big data technologies like Hadoop, Kafka, or Spark for processing large-scale data. Experience with data visualization tools such as Tableau, Power BI, or similar platforms for building reports More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage More ❯

ELT tools, APIs, and integration platforms. Deep knowledge of data modelling, warehousing, and real time analytics. Familiarity with big data technologies principals (e.g., Spark, Hadoop) and BI tools (e.g., Power BI, Tableau). Strong programming skills (e.g. SQL, Python, Java, or similar languages). Ability to exercise a substantial More ❯

experience : Experience of working as a Scala developer/engineer within the technology function of a Global Investment Bank. Experience migrating data applications from Hadoop to AWS Databricks. Seniority level Mid-Senior level Employment type Full-time Job function Information Technology Industries Technology, Information and Media #J-18808-Ljbffr More ❯

platforms (AWS, GCP, Azure) and cloud services for data storage, processing, and analytics. Nice-to-Have Requirements: Familiarity with big data technologies such as Hadoop, Kafka, and similar tools. Familiarity with version control systems like Git. Experience with GraphDB, MongoDB, SQL/NoSQL, MS Access, and other databases. Ability More ❯

platforms (AWS, GCP, Azure) and cloud services for data storage, processing, and analytics. Nice-to-Have Requirements Familiarity with big data technologies such as Hadoop, Kafka, and similar tools. Familiarity with version control systems like Git. Experience with GraphDB, MongoDB, SQL/NoSQL, MS Access, and other databases. Ability More ❯

sponsor visas. Preferred Skills and Experience Public sector experience Knowledge of cloud platforms (IBM Cloud, AWS, Azure) Experience with big data frameworks (Apache Spark, Hadoop) Data warehousing and BI tools (IBM Cognos, Tableau) Additional Details Seniority level: Mid-Senior level Employment type: Full-time Job function: Information Technology Industries More ❯

based data systems Clear communicator, able to translate complex data concepts to cross-functional teams Bonus points for experience with: Big data tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape storage More ❯

in cloud services and cloud-based data engineering tools: such as AWS, Azure, Microsoft Fabric and Databricks, as well as big data technologies like Hadoop and Spark. Experience in programming languages: including Python, PySpark and Scala. Experienced in mentoring and developing less experienced Data Engineers: guiding them to grow More ❯

Science, Engineering, Mathematics, Physics or a related field. Hands-on experience with LLMs, RAG, LangChain, or LlamaIndex. Experience with big data technologies such as Hadoop, Spark, or Kafka. The estimated total compensation range for this position is $75,000 - $90,000 ( USD base plus bonus). Actual compensation for More ❯

on data accuracy, quality, and reliability Desirable (Nice to Have): Background in defence, government, or highly regulated sectors Familiarity with Apache Kafka, Spark, or Hadoop Experience with Docker and Kubernetes Use of monitoring/alerting tools such as Prometheus, Grafana, or ELK Understanding of machine learning algorithms and data More ❯