76 to 100 of 467 Hadoop Jobs

languages such as Python, R, and SQL.+ In-depth experience with data manipulation and visualization libraries (e.g., Pandas, NumPy, Matplotlib, etc.).+ Solid understanding of big data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud).+ Strong expertise in the full data science lifecycle: data collection, preprocessing, model development, deployment, and monitoring.+ Experience in leading teams More ❯

orchestration tools like Apache Airflow or Cloud Composer. Hands-on experience with one or more of the following GCP data processing services: Dataflow (Apache Beam), Dataproc (Apache Spark/Hadoop), or Composer (Apache Airflow). Proficiency in at least one scripting/programming (e.g., Python, Java, Scala) for data manipulation and pipeline development. Scala is mandated in some cases. More ❯

orchestration tools like Apache Airflow or Cloud Composer. Hands-on experience with one or more of the following GCP data processing services: Dataflow (Apache Beam), Dataproc (Apache Spark/Hadoop), or Composer (Apache Airflow). Proficiency in at least one scripting/programming language (e.g., Python, Java, Scala) for data manipulation and pipeline development. Scala is mandated in some More ❯

orchestration tools like Apache Airflow or Cloud Composer. Hands-on experience with one or more of the following GCP data processing services: Dataflow (Apache Beam), Dataproc (Apache Spark/Hadoop), or Composer (Apache Airflow). Proficiency in at least one scripting/programming language (e.g., Python, Java, Scala) for data manipulation and pipeline development. Scala is mandated in some More ❯

of Scala. Familiarity with distributed computing frameworks such as Spark, KStreams, Kafka. Experience with Kafka and streaming frameworks. Understanding of monolithic vs. microservice architectures. Familiarity with Apache ecosystem including Hadoop modules (HDFS, YARN, HBase, Hive, Spark) and Apache NiFi. Experience with containerization and orchestration tools like Docker and Kubernetes. Knowledge of time-series or analytics databases such as Elasticsearch. More ❯

/KStreams/Kafka. Connect and Streaming Frameworks such as Kafka. Knowledge on Monolithic versus Microservice Architecture concepts for building large-scale applications. Familiar with the Apache suite including Hadoop modules such as HDFS, Yarn, HBase, Hive, Spark as well as Apache NiFi. Familiar with containerization and orchestration technologies such as Docker, Kubernetes. Familiar with Time-series or Analytics More ❯

evaluating exciting new technologies to design and build scalable real time data applications. Spanning the full data lifecycle and experience using mix of modern and traditional data platforms (e.g. Hadoop, Kafka, GCP, Azure, Teradata, SQL server) you'll get to work building capabilities with horizon-expanding exposure to a host of wider technologies and careers in data. Helping in … and non-relational databases to build data solutions, such as SQL Server/Oracle , experience with relational and dimensional data structures. Experience in using distributed frameworks ( Spark, Flink, Beam, Hadoop ). Proficiency in infrastructure as code (IaC) using Terraform . Experience with CI/CD pipelines and related tools/frameworks. Containerisation Good knowledge of containers ( Docker, Kubernetes etc More ❯

Data Engineer for Cloud Data Lake activities. The candidate should have industry experience (preferably in Financial Services) in navigating enterprise Cloud applications using distributed computing frameworks as Apache Spark, Hadoop, Hive. Working knowledgeoptimizing database performance, scalability, ensuring data security and compliance. Education & Preferred Qualifications Bachelor's/Master's Degree in a Computer Science, Engineering or Math or equivalent More ❯

practices for data engineering, including infrastructure-as-code (e.g., Terraform, CloudFormation), CI/CD pipelines, and monitoring (e.g., CloudWatch, Datadog). Familiarity with big data technologies like Apache Spark, Hadoop, or similar. ETL/ELT tools and creating common data sets across on-prem (IBMDatastage ETL) and cloud data stores Leadership & Strategy: Lead Data Engineering team(s) in designing More ❯

evaluating exciting new technologies to design and build scalable real time data applications. Spanning the full data lifecycle and experience using mix of modern and traditional data platforms (e.g. Hadoop, Kafka, GCP, Azure, Teradata, SQL server) you'll get to work building capabilities with horizon-expanding exposure to a host of wider technologies and careers in data. Helping in … and non-relational databases to build data solutions, such as SQL Server/Oracle , experience with relational and dimensional data structures Experience in using distributed frameworks ( Spark, Flink, Beam, Hadoop ) Proficiency in infrastructure as code (IaC) using Terraform Experience with CI/CD pipelines and related tools/frameworks Containerisation Good knowledge of containers ( Docker, Kubernetes etc) Cloud Experience More ❯

and managing end to end projects with diverse cross-functional teams Proven skills in translating analytics output to actionable recommendations Hands-on experience with modern distributed systems, including both Hadoop, Hive/SQL and Apache Spark Proficiency in creating reproducible analytic pipelines One or more data analytics/programming tools such as Python and R Proficiency with version control More ❯

build scalable data infrastructure, develop machine learning models, and create robust solutions that enhance public service delivery. Working in classified environments, you'll tackle complex challenges using tools like Hadoop, Spark, and modern visualisation frameworks while implementing automation that drives government efficiency. You'll collaborate with stakeholders to transform legacy systems, implement data governance frameworks, and ensure solutions meet … R; Collaborative, team-based development; Cloud analytics platforms e.g. relevant AWS and Azure platform services; Data tools hands on experience with Palantir ESSENTIAL; Data science approaches and tooling e.g. Hadoop, Spark; Data engineering approaches; Database management, e.g. MySQL, Postgress; Software development methods and techniques e.g. Agile methods such as SCRUM; Software change management, notably familiarity with git; Public sector More ❯

build scalable data infrastructure, develop machine learning models, and create robust solutions that enhance public service delivery. Working in classified environments, you'll tackle complex challenges using tools like Hadoop, Spark, and modern visualisation frameworks while implementing automation that drives government efficiency. You'll collaborate with stakeholders to transform legacy systems, implement data governance frameworks, and ensure solutions meet … R; Collaborative, team-based development; Cloud analytics platforms e.g. relevant AWS and Azure platform services; Data tools hands on experience with Palantir ESSENTIAL; Data science approaches and tooling e.g. Hadoop, Spark; Data engineering approaches; Database management, e.g. MySQL, Postgress; Software development methods and techniques e.g. Agile methods such as SCRUM; Software change management, notably familiarity with git; Public sector More ❯

build scalable data infrastructure, develop machine learning models, and create robust solutions that enhance public service delivery. Working in classified environments, you'll tackle complex challenges using tools like Hadoop, Spark, and modern visualisation frameworks while implementing automation that drives government efficiency. You'll collaborate with stakeholders to transform legacy systems, implement data governance frameworks, and ensure solutions meet … R; Collaborative, team-based development; Cloud analytics platforms e.g. relevant AWS and Azure platform services; Data tools hands on experience with Palantir ESSENTIAL; Data science approaches and tooling e.g. Hadoop, Spark; Data engineering approaches; Database management, e.g. MySQL, Postgress; Software development methods and techniques e.g. Agile methods such as SCRUM; Software change management, notably familiarity with git; Public sector More ❯

build scalable data infrastructure, develop machine learning models, and create robust solutions that enhance public service delivery. Working in classified environments, you'll tackle complex challenges using tools like Hadoop, Spark, and modern visualisation frameworks while implementing automation that drives government efficiency. You'll collaborate with stakeholders to transform legacy systems, implement data governance frameworks, and ensure solutions meet … R; Collaborative, team-based development; Cloud analytics platforms e.g. relevant AWS and Azure platform services; Data tools hands on experience with Palantir ESSENTIAL; Data science approaches and tooling e.g. Hadoop, Spark; Data engineering approaches; Database management, e.g. MySQL, Postgress; Software development methods and techniques e.g. Agile methods such as SCRUM; Software change management, notably familiarity with git; Public sector More ❯

Engineering, Mathematics, Finance, etc. Proficiency in Python, SQL , and one or more: R, Java, Scala Experience with relational/NoSQL databases (e.g., PostgreSQL, MongoDB) Familiarity with big data tools (Hadoop, Spark, Kafka), cloud platforms (Azure, AWS, GCP), and workflow tools (Airflow, Luigi) Bonus: experience with BI tools , API integrations , and graph databases Why Join Us? Work with large-scale More ❯

Engineering, Mathematics, Finance, etc. Proficiency in Python, SQL , and one or more: R, Java, Scala Experience with relational/NoSQL databases (e.g., PostgreSQL, MongoDB) Familiarity with big data tools (Hadoop, Spark, Kafka), cloud platforms (Azure, AWS, GCP), and workflow tools (Airflow, Luigi) Bonus: experience with BI tools , API integrations , and graph databases Why Join Us? Work with large-scale More ❯

. Hands-on experience with data warehousing solutions (Snowflake, BigQuery, Redshift, etc.). Knowledge of ETL/ELT frameworks, pipeline orchestration (Airflow, dbt), and big data technologies (Spark, Kafka, Hadoop, etc.) . Solid understanding of data governance, security, and compliance regulations (GDPR, ISO, etc.) . Strong programming skills in SQL, Python, or Scala . Experience working in agile and More ❯

preferably in a fast-paced and dynamic environment. Strong understanding of data modeling, database design, and SQL query optimization. Experience with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark, Kafka). Knowledge of cloud platforms and services, such as AWS, Azure, or Google Cloud Platform. Benefits: €90,000+ Company car Opportunity to work on innovative projects at More ❯

Engineering, Mathematics, Finance, etc. Proficiency in Python, SQL , and one or more: R, Java, Scala Experience with relational/NoSQL databases (e.g., PostgreSQL, MongoDB) Familiarity with big data tools (Hadoop, Spark, Kafka), cloud platforms (Azure, AWS, GCP), and workflow tools (Airflow, Luigi) Bonus: experience with BI tools , API integrations , and graph databases Why Join Us? Work with large-scale More ❯

with SQL and database technologies (incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical models − Ability to scale up More ❯

with SQL and database technologies (incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical models − Ability to scale up More ❯

with SQL and database technologies (incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical models − Ability to scale up More ❯

implementing data governance, security standards, and compliance practices. Strong understanding of metadata management, data lineage, and data quality frameworks. Preferred Skills & Knowledge: Familiarity with big data technologies such as Hadoop, Spark, or Kafka Excellent communication skills with the ability to explain complex data strategies to non-technical stakeholders. Outstanding problem-solving abilities and organizational skills. Certifications (Preferred/Desirable More ❯

is important) Latest Data Science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., TensorFlow, MXNet, scikit-learn) Software engineering practices (coding standards, unit testing, version control, code review) Hadoop distributions (Cloudera, Hortonworks), NoSQL databases (Neo4j, Elastic), streaming technologies (Spark Streaming) Data manipulation and wrangling techniques Development and deployment technologies (virtualisation, CI tools like Jenkins, configuration management with Ansible More ❯