1 to 25 of 103 Apache Spark Jobs with Hybrid or WFH Options

Profisee), Snowflake Data Integration, Azure Service Bus, Deltalake, BigQuery, Azure DevOps, Azure Monitor, Azure Data Factory, SQL Server, Azure DataLake Storage, Azure App Service, Apache Airflow, Apache Iceberg, Apache Spark, Apache Hudi, Apache Kafka, Power BI, BigQuery, Azure ML is a plus Experience with … Azure SQL Database, Cosmos DB, NoSQL, MongoDB Experience with Agile, DevOps methodologies Awareness and knowledge of ELT/ETL, DWH, APIs (RESTful), Spark APIs, FTP protocols, SSL, SFTP, PKI (Public Key Infrastructure) and Integration testing Skills and Abilities Knowledge of Python, SQL, SSIS, and Spark languages. Demonstrative ability more »

required) Experience with distributed message brokers using Kafka (required) Experience with high speed distributed computing frameworks such as AWS EMR, Hadoop, HDFS, S3, MapReduce, Apache Spark, Apache Hive, Kafka Streams, Apache Flink etc. (required) Experience working with various types of databases like Relational, NoSQL, Object-based more »

to develop unit test cases. Help in backlog grooming. Key skills: Extensive experience in developing Bigdata pipelines in cloud using Bigdata technologies such as Apache Spark Expertise in performing complex data transformation using Spark SQL queries Experience in orchestrating data pipelines using Apache Airflow Proficiency in more »

to develop unit test cases. Help in backlog grooming. Key skills: Extensive experience in developing Bigdata pipelines in cloud using Bigdata technologies such as Apache Spark Expertise in performing complex data transformation using Spark SQL queries Experience in orchestrating data pipelines using Apache Airflow Proficiency in more »

and product development, encompassing experience in both stream and batch processing. Designing and deploying production data pipelines, utilizing languages such as Java, Python, Scala, Spark, and SQL. In addition, you should have proficiency or familiarity with: Scripting and data extraction via APIs, along with composing SQL queries. Integrating data more »

and product development, encompassing experience in both stream and batch processing. · Designing and deploying production data pipelines, utilizing languages such as Java, Python, Scala, Spark, and SQL. In addition, you should have proficiency or familiarity with: · Scripting and data extraction via APIs, along with composing SQL queries. · Integrating data more »

Terraform/Docker/Kubernetes. Write software using either Java/Scala/Python . The following are nice to have, but not required - Apache Spark jobs and pipelines. Experience with any functional programming language. Database design concepts. Writing and analysing SQL queries. Application overVIOOH Our recruitment team more »

and able to guide how one could deploy infrastructure into different environments. Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes) Ability to more »

and able to guide how one could deploy infrastructure into different environments. Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes) Ability to more »

emphasis on Pyspark and Databricks for this particular role. Technical Skills Required: Azure (ADF, Functions, Blob Storage, Data Lake Storage, Azure Data Bricks) Databricks Spark Delta Lake SQL Python PySpark ADLS Day To Day Responsibilities: Extensive experience in designing, developing, and managing end-to-end data pipelines, ETL (Extract more »

in programming languages and tools for data analysis, such as Python, R, and SQL You must be proficient in big data technologies, such as Spark, Kafka and/or Hadoop. A strong understanding of statistical analysis, predictive modelling, machine learning algorithms, and data development and optimisation is essential You more »

with data ingestion tools such as Airbyte and Fivetran, accommodating a wide array of data sources. Mastery of large-scale data processing techniques using Spark or Dask. Strong programming skills in Python, Scala, C#, or Java, and adeptness with cloud SDKs and APIs. Deep understanding of AI/ML more »

for seamless data integration. * Understanding of DevOps best practices for SQL and Power BI projects, including DACPAC, CI/CD, and versioning. * Familiarity with Apache Spark for big data processing. * Additional development experience in Python or related technologies. * Experience gained within a Media, Travel or Broadcast Media sectors more »

quality testing frameworks. Proficiency in Python and familiarity with modern software engineering practices, including 12factor, CI/CD, and Agile methodologies. Deep understanding of Spark (PySpark), Python (Pandas), orchestration software (e.g. Airflow, Prefect) and databases, data lakes and data warehouses. Experience with cloud technologies, particularly AWS Cloud services, with more »

pivotal role in designing, building, and maintaining their data infrastructure while collaborating closely with senior stakeholders across the organisation. Your expertise in Azure, Databricks, Spark, Python, and data modelling will be critical in driving the success of their data initiatives. Key Responsibilities: Lead the complete development cycle of data … comprehensive of data modelling, data warehousing principles, and the innovative Lakehouse architecture. Exceptional proficiency in ETL methodologies, preferably utilising Azure Databricks or equivalent technologies (Spark, Spark SQL, Python, SQL), including deep insight into ETL/ELT design patterns. Proficient in Databricks, SQL, and Python, with a robust understanding more »

Essential Skills Proven experience as a Data Engineer Well versed in the following: cloud-based data storage solutions, data lakes, customer data platforms. (Python, Spark, SQL, Cloud Data Environments such as AWS, GCP, Azure) Good understanding of data modelling methods and data partitioning and compaction methods in Data Lake more »

etc.) MLOps experience Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure Understanding of Big Data Technologies (Hadoop, Spark etc) Experience with Cloud platforms (AWS, GCP or Azure) This is a fully remote role, but may require very occasional travel (once a month more »

APIs, infrastructure design load balancing, VMs, PostgreSQL, vector dbs. Senior ML Learning Engineer desirable skills: Version control (Git), computer vision libraries, Big Data (Hadoop, Spark), Cloud AWS, Google Cloud, Azure, and a knowledge of secure coding techniques PCI-DSS, PA-DSS, ISO27001. This is a fantastic opportunity to join more »

tools such as Informatica MDM, Informatica AXON, Informatica EDC, and Collibra • MySQL, SQL Server, Oracle, Snowflake, PostgreSQL and NoSQL databases • Programming languages such as Spark or Python • Amazon Web Services, Microsoft Azure or Google Cloud and distributed processing technologies such as Hadoop Benefits : • Base Salary more »

Modelling. Experience with at least one or more of these programming languages: Python, Scala/Java Experience with distributed data and computing tools, mainly Apache Spark & Kafka Understanding of critical path approaches, how to iterate to build value, engaging with stakeholders actively at all stages. Able to deal more »

frameworks (TensorFlow, PyTorch) Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure Understanding of Big Data Technologies (Hadoop, Spark etc) Experience with Cloud platforms (AWS, GCP or Azure) This is a fully remote role, but may require very occasional travel (once a month more »

Linux, APIs, infrastructure design load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer desirable skills: Version control (Git), computer vision libraries, Big Data (Hadoop, Spark), Cloud AWS, Google Cloud, Azure, and a knowledge of secure coding techniques PCI-DSS, PA-DSS, ISO27001. Note: as there are actually two roles more »

mining, data analysis, and strong software engineering skills. Strong understanding of Data Engineering Proficiency in AWS, data warehousing (Snowflake, Databricks, Redshift), big data frameworks (Spark, Kafka), container orchestration platforms (Kubernetes), and data integration/ETL tools. Strong written and verbal communication skills, with the ability to explain technical concepts more »

of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling and insurance are a plus. Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow more »

solutions Proficiency in data pipeline orchestration across hybrid environments, leveraging the latest in Azure and allied technologies. Expertise in data processing with tools like Spark or Dask, and fluency in Python, Scala, C#, or Java. Expertise in DevOps and CI/CD automation , ensuring seamless deployment with tools like more »