1 to 25 of 116 Hadoop Jobs

of the following: Python, SQL, Java Commercial experience in client-facing projects is a plus, especially within multi-disciplinary teams Deep knowledge of database technologies: Distributed systems (e.g., Spark, Hadoop, EMR) RDBMS (e.g., SQL Server, Oracle, PostgreSQL, MySQL) NoSQL (e.g., MongoDB, Cassandra, DynamoDB, Neo4j) Solid understanding of software engineering best practices - code reviews, testing frameworks, CI/CD, and More ❯

quality-driven mindset Experience with CI/CD pipelines and writing complex queries Excellent communication and collaboration in fast-paced teams Bonus points for: Experience with big data technologies (Hadoop, Spark, Kafka) Knowledge of best practices in coding, data versioning, monitoring, and optimisation Understanding of cloud data services and distributed/parallel computing Workflow scheduling/monitoring experience Relevant More ❯

ETL processes. Proficiency in Python. Experience with cloud platforms (AWS, Azure, or GCP). Knowledge of data modelling, warehousing, and optimisation. Familiarity with big data frameworks (e.g. Apache Spark, Hadoop). Understanding of data governance, security, and compliance best practices. Strong problem-solving skills and experience working in agile environments. Desirable: Experience with Docker/Kubernetes, streaming data (Kafka More ❯

ETL processes. Proficiency in Python. Experience with cloud platforms (AWS, Azure, or GCP). Knowledge of data modelling, warehousing, and optimisation. Familiarity with big data frameworks (e.g. Apache Spark, Hadoop). Understanding of data governance, security, and compliance best practices. Strong problem-solving skills and experience working in agile environments. Desirable: Experience with Docker/Kubernetes, streaming data (Kafka More ❯

data modelling, warehousing, and performance optimisation. Proven experience with cloud platforms (AWS, Azure, or GCP) and their data services. Hands-on experience with big data frameworks (e.g. Apache Spark, Hadoop). Strong knowledge of data governance, security, and compliance. Ability to lead technical projects and mentor junior engineers. Excellent problem-solving skills and experience in agile environments. Desirable: Experience More ❯

data modelling, warehousing, and performance optimisation. Proven experience with cloud platforms (AWS, Azure, or GCP) and their data services. Hands-on experience with big data frameworks (e.g. Apache Spark, Hadoop). Strong knowledge of data governance, security, and compliance. Ability to lead technical projects and mentor junior engineers. Excellent problem-solving skills and experience in agile environments. Desirable: Experience More ❯

experience within either Flask, Tornado or Django, Docker Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. Data acquisition and development of data sets and improving data quality Preparing data for predictive and prescriptive modelling Hands on coding experience, such as Python Reporting tools More ❯

experience within either Flask, Tornado or Django, Docker Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. Data acquisition and development of data sets and improving data quality Preparing data for predictive and prescriptive modelling Hands on coding experience, such as Python Reporting tools More ❯

communication skills We're excited if you have 7+ years of experience delivering multi tier, highly scalable, distributed web applications Experience working with Distributed computing frameworks knowledge: Hive/Hadoop, Apache Spark, Kafka, Airflow Working with programming languages Python , Java, SQL. Working on building ETL (Extraction Transformation and Loading) solution using PySpark Experience in SQL/NoSQL database design More ❯

of experience may be considered in lieu of a degree. Proficiency in programming languages like Python or Java, strong SQL skills, and knowledge of big data tools like Apache Hadoop, Spark, or Kafka. Experience with cloud platforms (AWS, Azure, GCP) and data warehousing solutions (Snowflake, Redshift, BigQuery) Self-driven and have demonstrated the ability to work independently with minimum More ❯

Understanding of ML development workflow 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 frameworks like Great Expectations, dbt More ❯

providers, preferably Azure (AWS/GCP also valued). Experience with modern data lakehouse concepts and architectures. Experience ingesting and transforming data from sources such as Kafka, REST APIs, Hadoop, etc. Experience with data pipeline orchestration tools (Azure Data Factor or similar). Experience implementing ETL/ELT pipelines using modern data lakehouse solutions. Experience with data quality, observability More ❯

problem-solving skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if More ❯

problem-solving skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if More ❯

to support analytical and business goals. Monitor, troubleshoot , and enhance data performance and infrastructure. Key Skills & Experience: Strong experience with SQL/NoSQL databases, data warehousing, and big data (Hadoop, Spark). Proficient in Python, Java, or Scala with solid OOP and design pattern understanding. Expertise in ETL tools, DevOps and orchestration frameworks (Airflow, Apache NiFi). Hands-on More ❯

in data engineering, with a strong emphasis on data design and architecture. Proven proficiency in SQL and experience with relational databases. Practical experience with big data technologies such as Hadoop or Spark. In-depth understanding of data warehousing concepts and ETL frameworks. Familiarity with cloud platforms including AWS, Azure, or GCP. Strong analytical and problem-solving skills, with the More ❯

Azure Data FactoryExperience in Unix/Linux environments and shell scripting.Excellent problem-solving, analytical, and communication skills. Preferred SkillsExperience with Informatica Intelligent Cloud Services (IICSExposure to big data platforms (Hadoop, Spark) or data lake architectures.Familiarity with Agile or Scrum methodologies.Background in finance, healthcare, or retail data environments is a plus.Experience integrating data from cloud platforms (AWS, Azure, GCP More ❯

Security project experience. Experience with Palantir Foundry (full training provided). Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real More ❯

Security project experience. Experience with Palantir Foundry (full training provided). Familiarity with AI/ML Ops pipelines , real-time analytics, or edge deployments. Big Data stack knowledge (e.g., Hadoop, Spark, Kafka). GenAI/LLM experience (e.g., AWS Bedrock, LangChain). Why this is a great move 🌳 Mission & impact: Work on projects where data-driven decisions have real More ❯

AI model development. Expertise in Python, R, or Julia, with proficiency in pandas, NumPy, SciPy, scikit-learn, TensorFlow, or PyTorch. Experience with SQL, NoSQL, and big data technologies (Spark, Hadoop, Snowflake, Databricks, etc.). Strong background in statistical modelling, probability theory, and mathematical optimization. Experience deploying machine learning models to production (MLOps, Docker, Kubernetes, etc.). Familiarity with AWS More ❯

such as Python, R, and SQL for data analysis and model development. Experience working with cloud computing platforms including AWS and Azure, and familiarity with distributed computing frameworks like Hadoop and Spark. Deep understanding of supply chain operations and the ability to apply data science methods to solve real-world business problems effectively. Strong foundational knowledge in mathematics and More ❯

tools and libraries (e.g., Power BI) · Background in database administration or performance tuning · Familiarity with data orchestration tools, such as Apache Airflow · Previous exposure to big data technologies (e.g., Hadoop, Spark) for large data processing · Strong analytical skills, including a thorough understanding of how to interpret customer business requirements and translate them into technical designs and solutions. · Strong communication More ❯

in Python, R, SQL, and experience with cloud-based ML platforms such as Azure ML, AWS, or GCP. Hands-on experience with data pipeline technologies (Azure Data Factory, Spark, Hadoop) and business intelligence tools (Power BI, Tableau, or SAP Analytics Cloud). Strong understanding of machine learning model lifecycle management, from design through deployment and monitoring. Exceptional communication and More ❯

Flows, Conduct>It, Express>It, Metadata Hub, and PDL. Hands-on experience with SQL , Unix/Linux shell scripting , and data warehouse concepts . Familiarity with big data ecosystems (Hadoop, Hive, Spark) and cloud platforms (AWS, Azure, GCP) is a plus. Proven ability to troubleshoot complex ETL jobs and resolve performance issues. Experience working with large-scale datasets and More ❯

for data engineering. A detail-oriented mindset and strong problem-solving skills. Degree in Computer Science , Engineering , or a related field. Bonus Skills: Experience with big data tools (e.g., Hadoop , Spark ). Exposure to machine learning workflows . Understanding of prompt engineering concepts. Benefits: 25 days annual leave (plus bank holidays). An additional day of paid leave for More ❯