. Hands-on experience with open-source ETL, and data pipeline orchestration tools such as Apache Airflow and Nifi. Experience with large scale/Big Data technologies, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka. Experience with workflow orchestration tools like Apache Airflow. Experience with containerisation using Docker and deployment on Kubernetes. Experience with NoSQL and graph databases. Unix More ❯
cloud platforms (e.g., AWS , Azure , GCP ). Experience deploying ML models or managing AI/ML workflows in production. Working knowledge of big data technologies like Spark , Hive , or Hadoop . Familiarity with MLOps tools (e.g., MLflow , Kubeflow , DataRobot ). Education Bachelor’s degree in Computer Science , Software Engineering , or a related technical field — or equivalent practical experience. Why More ❯
cloud platforms (e.g., AWS , Azure , GCP ). Experience deploying ML models or managing AI/ML workflows in production. Working knowledge of big data technologies like Spark , Hive , or Hadoop . Familiarity with MLOps tools (e.g., MLflow , Kubeflow , DataRobot ). Education Bachelor’s degree in Computer Science , Software Engineering , or a related technical field — or equivalent practical experience. Why More ❯
and statistical packages. Strong analytical, problem-solving, and critical thinking skills. 8.Experience with social media analytics and understanding of user behaviour. 9.Familiarity with big data technologies, such as ApacheHadoop, Apache Spark, or Apache Kafka. 10.Knowledge of AWS machine learning services, such as Amazon SageMaker and Amazon Comprehend. 11.Experience with data governance and security best practices in AWS. 12Excellent More ❯
London, England, United Kingdom Hybrid / WFH Options
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and statistical packages. Strong analytical, problem-solving, and critical thinking skills. 8.Experience with social media analytics and understanding of user behaviour. 9.Familiarity with big data technologies, such as ApacheHadoop, Apache Spark, or Apache Kafka. 10.Knowledge of AWS machine learning services, such as Amazon SageMaker and Amazon Comprehend. 11.Experience with data governance and security best practices in AWS. 12Excellent More ❯
time data pipelines for processing large-scale data. Experience with ETL processes for data ingestion and processing. Proficiency in Python and SQL. Experience with big data technologies like ApacheHadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale ML inference pipelines into production More ❯
environment. Preferred Qualifications: AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect - Associate. Experience with Airflow for workflow orchestration. Exposure to big data frameworks such as Apache Spark, Hadoop, or Presto. Hands-on experience with machine learning pipelines and AI/ML data engineering on AWS. Benefits: Competitive salary and performance-based bonus structure. Join a rapidly expanding More ❯
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 ❯
5+ years of experience working on mission critical data pipelines and ETL systems. 5+ years of hands-on experience with big data technology, systems and tools such as AWS, Hadoop, Hive, and Snowflake Expertise with common Software Engineering languages such as Python, Scala, Java, SQL and a proven ability to learn new programming languages Experience with workflow orchestration tools More ❯
Redshift, EMR, Glue). Familiarity with programming languages such as Python or Java. Understanding of data warehousing concepts and data modeling techniques. Experience working with big data technologies (e.g., Hadoop, Spark) is an advantage. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Benefits Enhanced leave - 38 days inclusive of 8 UK Public Holidays Private Health Care More ❯
Strong knowledge of data architecture, data modeling, and ETL/ELT processes. Proficiency in programming languages such as Python, Java, or Scala. Experience with big data technologies such as Hadoop, Spark, and Kafka. Familiarity with cloud platforms like AWS, Azure, or Google Cloud. Excellent problem-solving skills and the ability to think strategically. Strong communication and interpersonal skills, with More ❯
deploy your pipelines and proven 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 and experience with code and More ❯
Statistics, Maths or similar Science or Engineering discipline Strong Python and other programming skills (Java and/or Scala desirable) Strong SQL background Some exposure to big data technologies (Hadoop, spark, presto, etc.) NICE TO HAVES OR EXCITED TO LEARN: Some experience designing, building and maintaining SQL databases (and/or NoSQL) Some experience with designing efficient physical data More ❯
cloud environment and various platforms, including Azure, SQL Server. NoSQL databases is good to have. Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience with DataOps practices and tools, including CI/CD for data pipelines. Experience in medallion data architecture and other similar data modelling approaches. Experience with More ❯
Azure Functions, Azure SQL Database, HDInsight, and Azure Machine Learning Studio. Data Storage & Databases: SQL & NoSQL Databases: Experience with databases like PostgreSQL, MySQL, MongoDB, and Cassandra. Big Data Ecosystems: Hadoop, Spark, Hive, and HBase. Data Integration & ETL: Data Pipelining Tools: Apache NiFi, Apache Kafka, and Apache Flink. ETL Tools: AWS Glue, Azure Data Factory, Talend, and Apache Airflow. AI More ❯
Experience of Relational Databases and Data Warehousing concepts. Experience of 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. You must be: Willing to work on client sites, potentially for extended periods. Willing to More ❯
and-loss forecasting and planning for the Physical Consumer business. We are building the next generation Business Intelligence solutions using big data technologies such as Apache Spark, Hive/Hadoop, and distributed query engines. As a Data Engineer in Amazon, you will be working in a large, extremely complex and dynamic data environment. You should be passionate about working More ❯
in a similar role. - 3+ years of experience with data modeling, data warehousing, ETL/ELT pipelines and BI tools. - Experience with cloud-based big data technology stacks (e.g., Hadoop, Spark, Redshift, S3, EMR, Glue, SageMaker, DynamoDB etc.) - Knowledge of data management and data storage principles. - Expert-level proficiency in writing and optimizing SQL. - Ability to write code in More ❯
in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and big data technolo g ies (e. g ., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Goo g le Cloud and cloud-based data services (e.g ., AWS Redshift, Azure Synapse Analytics, Goog More ❯
in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and big data technolo g ies (e. g ., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Goo g le Cloud and cloud-based data services (e.g ., AWS Redshift, Azure Synapse Analytics, Goog More ❯
development e.g. R, Python Strong knowledge of deploying end-to-end machine learning models in Databricks utilizing Pyspark, MLflow and workflows Strong knowledge of data platforms and tools, including Hadoop, Spark, SQL, and NoSQL databases Communicate algorithmic solutions in a clear, understandable way. Leverage data visualization techniques and tools to effectively demonstrate patterns, outliers and exceptional conditions in the More ❯
modern data architectures, Lambda type architectures - Proficiency in writing and optimizing SQL - Knowledge of AWS services including S3, Redshift, EMR, Kinesis and RDS. - Experience with Open Source Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.) - Ability to write code in Python, Ruby, Scala or other platform-related Big data technology - Knowledge of professional software engineering practices & best practices for More ❯
Snowflake. Understanding of cloud platform infrastructure and its impact on data architecture. Data Technology Skills: A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems. Knowledge of programming languages such as Python, R, or Java is beneficial. Exposure to ETL/ELT processes, SQL, NoSQL databases is a nice-to-have, providing a More ❯
functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at payal.c@hcltech.com More ❯
functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at payal.c@hcltech.com More ❯
