1 to 25 of 154 Hadoop Jobs

design and data modeling experience, and advanced SQL across large, complex datasets. Extensive experience with big data technologies and cloud data warehouses (Snowflake, BigQuery, Hadoop/Hive) at terabyte-and-growing scale. Experience building reusable frameworks, platforms, or tooling that other engineers depend on (not just point solutions).Hands ...

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 Reporting tools (e.g. Tableau, PowerBI ...

Programming-related field* Experience influencing technical decisions and supporting capability growth.* Experience with CI/CD practices* Experience with big data tools e.g. Spark, Hadoop, NiFi* Exposure to infrastructure scaling e.g. Kubernetes* Exposure to Ansible and Terraform* Understanding of ML algorithms and deployment* Experience with SQL Server high-availability ...

experience in their technologies You have experience in database technologies including writing complex queries against their (relational and non-relational) data stores (e.g. Postgres, Hadoop, Elasticsearch, Graph databases), and designing the database schemas to support those queries You have a good understanding of coding best practices and design patterns ...

Science or a related field is preferred. Preferred Skills Familiarity with cloud services like AWS, Google Cloud, or Azure. Experience with big data tools: Hadoop, Spark, Kafka, etc. Knowledge of data integration tools like Informatica, Talend, etc. Understanding of machine learning algorithms and statistics. Experience with data visualization tools ...

NoSQL)* Experience with cloud technologies* Experience with cloud platforms* Experience with CI/CD practices* Experience with big data tools e.g. Spark, Hadoop, NiFi* Experience managing direct reports, providing regular guidance and performance feedback* Ability to create delivery plans with estimated timelines for personal and team workloads* Experience supporting ...

NoSQL) Experience with cloud technologies Experience with cloud platforms Experience with CI/CD practices Experience with big data tools e.g. Spark, Hadoop, NiFi Experience managing direct reports, providing regular guidance and performance feedback Ability to create delivery plans with estimated timelines for personal and team workloads Experience supporting ...

experience building, scaling, and shipping large-scale data platforms in production. Deep practical experience with distributed data processing frameworks (e.g., Apache Spark, Flink, Hadoop). Strong expertise in message brokers and event streaming platforms (e.g., Apache Kafka, Kinesis). End-to-end exposure to data pipeline lifecycle development, including ...

experience building, scaling, and shipping large-scale data platforms in production. Deep practical experience with distributed data processing frameworks (e.g., Apache Spark, Flink, Hadoop).Strong expertise in message brokers and event streaming platforms (e.g., Apache Kafka, Kinesis).End-to-end exposure to data pipeline lifecycle development, including extensive experience ...

Skills Programming: Proficiency in Python, Java, Scala, or similar languages. Big Data Technologies: Hands-on experience with big data tools e.g. (Databricks, Apache Spark, Hadoop). Cloud Platforms: Familiarity with AWS, Azure, GCP, or other cloud ecosystems for data engineering tasks. Expertise in relational databases (e.g. postgres, sql server ...

Databases and Data Warehousing concepts. Enterprise ETL tools such as Informatica, Talend, Datastage or Alteryx. Project experience using the any of the following technologies: Hadoop, Spark, Scala, Oracle, Pega, Salesforce. Cross and multi-platform experience. Team building and leading. Qualifications You must be: Willing to work on client sites ...

phases of the system development life cycle Experience with major database and big data platforms (e.g. RDS, Aurora, Redshift, Data bricks, MySQL, Oracle, PostgresSQL, Hadoop, Snowflake, etc.) Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.) Understanding of modern data warehouse capabilities and technologies such ...

Degree in STEM, Data, AI, or Programming-related field Experience influencing technical decisions and supporting capability growth. Experience with big data tools e.g. Spark, Hadoop, NiFi Exposure to Ansible and Terraform Understanding of ML algorithms and deployment ...

scale ETL development. Proficiency in SQL and programming languages such as Python, Java, or Scala. Hands‐on experience with big data frameworks (e.g., Spark, Hadoop, Flink) and cloud platforms (AWS, GCP, or Azure). Familiarity with data warehouse technologies (e.g., Snowflake, Redshift, BigQuery) and workflow orchestration tools (e.g., Airflow ...

Data bricks, Data Lake, Logic Apps and Data Factory Experience migrating or transforming legacy solutions to Public Cloud desirable Understanding of Big Data technologies (Hadoop, Spark) Familiarity with infrastructure considerations for data and system integration Broad knowledge of the design and implementation of applications' build, release, deployment, and configuration ...

Python, SQL, JavaCommercial experience in client-facing projects is a plus, especially within multi-disciplinary teamsDeep 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 ...

Experience with Microsoft Azure a plus: Azure SQL Database, Analysis Services, Databricks, Data Lake, Logic Apps and Data Factory Understanding of Big Data technologies (Hadoop, Spark) Able to create rich visualisations that appropriately represent the underlying datasets. Review and align the reporting attributes against the Enterprise and conceptual data ...

comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes-based deployment approaches where relevant You will also work with ...

Experience with data warehousing concepts and technologies (e.g., Azure Synapse Analytics, Azure Data Lake Storage). Familiarity with big data technologies and frameworks (e.g., Hadoop, Spark) is a plus. Knowledge of data governance and data security best practices. Strong problem-solving skills and attention to detail. Excellent communication ...

Experience with Microsoft Azure (a plus): Azure SQL Database, Analysis Services, Databricks, Data Lake, Logic Apps and Data Factory. Understanding of big data technologies (Hadoop, Spark). Able to create rich visualisations that appropriately represent the underlying datasets. Review and align the reporting attributes against the enterprise and conceptual ...

Experience with Microsoft Azure a plus: Azure SQL Database, Analysis Services, Databricks, Data Lake, Logic Apps and Data Factory Understanding of Big Data technologies (Hadoop, Spark) Able to create rich visualisations that appropriately represent the underlying datasets. Review and align the reporting attributes against the Enterprise and conceptual data ...

comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes‐based deployment approaches where relevant What We Are Looking ...

decisions and the trade‐offs behind them. Demonstrable experience leading data estate modernisation, such as moving from legacy data warehouses, on‐premises databases or Hadoop to modern cloud or hybrid data platforms. Deep expertise in at least one modern data platform (Databricks, Snowflake or Microsoft Fabric), plus a working ...

decisions and the trade-offs behind them. Demonstrable experience leading data estate modernisation, such as moving from legacy data warehouses, on-premises databases or Hadoop to modern cloud or hybrid data platforms. Deep expertise in at least one modern data platform (Databricks, Snowflake or Microsoft Fabric), plus a working ...

Oracle, Snowflake, Databricks). Experience with data integration (ETL/ELT, APIs). Familiarity with cloud data platforms (AWS, Azure, GCP) and big data (Hadoop, Spark, Kafka) is a plus. Domain Knowledge Exceptional understanding of the Funds business lifecycle, financial instruments, market data, and investment operations. In-depth knowledge ...