1 to 25 of 62 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 ❯

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 ❯

data modelling tools, data warehousing, ETL processes, and data integration techniques. · Experience with at least one cloud data platform (e.g. AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark). · Strong knowledge of data workflow solutions like Azure Data Factory, Apache NiFi, Apache Airflow etc · Good knowledge of stream and batch processing solutions like Apache Flink, Apache 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

/GCP/Azure). Hands-on experience with Unix-based command line and DevOps tools (Git, Docker, Kubernetes). Hands-on experience with big data technologies (e.g. Spark, Hadoop, Databricks). Experience with coaching/mentoring other engineers. Prior experience in Management Consulting is a strong plus. Willingness to travel and work at local and international clients. Fluency More ❯

Experience with cloud based infrastructures (AWS/GCP/Azure). Knowledge of Unix command line and DevOps tools (Git, Docker, Kubernetes). Experience with big data technologies (Spark, Hadoop, Databricks). Experience coaching/mentoring other engineers. Prior experience in management consulting is a strong plus. Willingness to travel and work at local and international clients. Fluency in More ❯

/GCP/Azure). Hands-on experience with Unix-based command line and DevOps tools (Git, Docker, Kubernetes). Hands-on experience with big data technologies (e.g. Spark, Hadoop, Databricks). Experience with coaching/mentoring other engineers. Prior experience in Management Consulting is a strong plus. Willingness to travel and work at local and international clients. Fluency More ❯

years' experience working with dbt.3+ years of experience with orchestration tooling (Airflow, Prefect, Dagster).Strong programming skills in languages such as Python or Java.Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka, Delta Lake, Iceberg, Arrow, Data Fusion).Familiarity with data governance tooling such as Monte Carlo, Atlan.Excellent problem-solving and analytical skills.Strong communication and interpersonal skills.Ability to work More ❯

in data modelling, data warehousing, and ETL development. Hands-on experience with Azure Data Factory, Azure Data Lake, and Azure SQL Database. Exposure to big data technologies such as Hadoop, Spark, and Databricks. Experience with Azure Synapse Analytics or Cosmos DB. Familiarity with data governance frameworks (e.g., GDPR, HIPAA). Experience implementing CI/CD pipelines using Azure DevOps More ❯

in data modelling, data warehousing, and ETL development. Hands-on experience with Azure Data Factory, Azure Data Lake, and Azure SQL Database. Exposure to big data technologies such as Hadoop, Spark, and Databricks. Experience with Azure Synapse Analytics or Cosmos DB. Familiarity with data governance frameworks (e.g., GDPR, HIPAA). Experience implementing CI/CD pipelines using Azure DevOps More ❯

years of experience in a customer facing technical role and a working experience in: Distributed systems and massively parallel processing technologies and concepts such as Snowflake, Teradata, Spark, Databricks, Hadoop, Oracle, SQL Server, and performance optimisation Data strategies and methodologies such as Data Mesh, Data Vault, Data Fabric, Data Governance, Data Management, Enterprise Architecture Data organisation and modelling concepts More ❯

for shaping data ecosystems and driving high impact solutions. Direct experience with cloud data technologies (Snowflake, AWS, Azure) highly valuable; background in SQL Server, MySQL, Postgres, NoSQL, Oracle or Hadoop also welcome. In depth knowledge of database structures, data analysis and data mining. Strong understanding of data warehousing, data lakes, ETL/ELT processes and big data technologies. Proficiency More ❯

the IC. Expert proficiency in Python (or similar languages) and experience with data science libraries (TensorFlow, PyTorch, Pandas, NumPy). Strong experience with big data processing tools (e.g., Spark, Hadoop, AWS or Azure cloud platforms). Expertise in working with geospatial data formats (e.g., GeoTIFF, Shapefiles, WMS, WFS) and spatial libraries (e.g., GeoPandas, Rasterio, GDAL). Advance experience in More ❯

Executives. Experience with manipulating massive scale structured and unstructured data. Experience in creating and maintaining business-critical data warehouse tables using SQL. Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.). Background in at least one programming language (e.g., R, Python, Java, Scala, PHP, JavaScript). Suggested Skills: Data analytics Collaboration More ❯