24 of 24 Spark SQL Jobs in London

experiences, powered by best-in-class understanding of customer behavior and automation. Our work spans multiple technical disciplines: from deep-dive analytics using SQL and Spark SQL for large-scale data processing, to building automated marketing solutions with Python, Lambda, React.js, and leveraging internal … results to senior leadership. Experience with data visualization using Tableau, Quicksight, or similar tools. Experience in scripting for automation (e.g. Python) and advanced SQL skills. Experience programming to extract, transform and clean large (multi-TB) data sets. Experience with statistical analytics and programming languages such as R, Python … science, machine learning and data mining. Experience with theory and practice of design of experiments and statistical analysis of results. Experience with Python, Spark SQL, QuickSight, AWS Lambda & React.js - Core tools of team. Amazon is an equal opportunities employer. We believe passionately that employing a diverse More ❯

we drive improvements in how millions of customers discover and evaluate products. Our work spans multiple technical disciplines: from deep-dive analytics using SQL and Spark SQL for large-scale data processing, to building automated marketing solutions with Python, Lambda, React.js, and leveraging internal … results to senior leadership. - Experience with data visualization using Tableau, Quicksight, or similar tools. - Experience in scripting for automation (e.g. Python) and advanced SQL skills. - Experience programming to extract, transform and clean large (multi-TB) data sets. - Experience with statistical analytics and programming languages such as R, Python … science, machine learning and data mining. - Experience with theory and practice of design of experiments and statistical analysis of results. - Experience with Python, Spark SQL, QuickSight, AWS Lambda & React.js - Core tools of team. More ❯

architectures that business engineering teams buy into and build their applications around. Required Qualifications, Capabilities, and Skills: Experience across the data lifecycle with Spark-based frameworks for end-to-end ETL, ELT & reporting solutions using key components like Spark SQL & Spark Streaming. … end-to-end engineering experience supported by excellent tooling and automation. Preferred Qualifications, Capabilities, and Skills: Good understanding of the Big Data stack (Spark/Iceberg). Ability to learn new technologies and patterns on the job and apply them effectively. Good understanding of established patterns, such as More ❯

role: This role sits within the Group Enterprise Systems (GES) Technology team. The right candidate would be an experienced Microsoft data warehouse developer (SQL Server, SSIS, SSAS) who can work both independently and as a member of a team to deliver enterprise-class data warehouse solutions and analytics … data models. Build and maintain automated pipelines to support data solutions across BI and analytics use cases. Work with Enterprise-grade technology, primarily SQL Server 2019 and potentially Azure technologies. Build patterns, common ways of working, and standardized data pipelines for DLG to ensure consistency across the organization. … Essential Core Technical Experience: 5 to 10+ years' extensive experience in SQL Server data warehouse or data provisioning architectures. Advanced SQL query writing & SQL procedure experience. Experience developing ETL solutions in SQL Server including SSIS & T-SQL. Experience in Microsoft BI technologies More ❯

engineers to develop scalable solutions that enhance data accessibility and efficiency across the organisation. Key Responsibilities Design, build, and maintain data pipelines using SQL, Python, and Spark . Develop and manage data warehouse and lakehouse solutions for analytics, reporting, and machine learning. Implement ETL/ELT … 6+ years of experience in data engineering within large-scale digital environments. Strong programming skills in Python, SQL, and Spark (SparkSQL) . Expertise in Snowflake and modern data architectures. Experience designing and managing data pipelines, ETL, and ELT workflows . Knowledge of AWS services such as More ❯

scalable data pipelines and infrastructure using AWS (Glue, Athena, Redshift, Kinesis, Step Functions, Lake Formation). Utilise PySpark for distributed data processing, ETL, SQL querying, and real-time data streaming. Architect and implement robust data solutions for analytics, reporting, machine learning, and data science initiatives. Establish and enforce … including Glue, Athena, Redshift, Kinesis, Step Functions, and Lake Formation. Strong programming skills in Python and PySpark for data processing and automation. Extensive SQL experience (Spark-SQL, MySQL, Presto SQL) and familiarity with NoSQL databases (DynamoDB, MongoDB, etc.). Proficiency in Infrastructure More ❯

scalable data pipelines and infrastructure using AWS (Glue, Athena, Redshift, Kinesis, Step Functions, Lake Formation). Utilise PySpark for distributed data processing, ETL, SQL querying, and real-time data streaming. Architect and implement robust data solutions for analytics, reporting, machine learning, and data science initiatives. Establish and enforce … including Glue, Athena, Redshift, Kinesis, Step Functions, and Lake Formation. Strong programming skills in Python and PySpark for data processing and automation. Extensive SQL experience (Spark-SQL, MySQL, Presto SQL) and familiarity with NoSQL databases (DynamoDB, MongoDB, etc.). Proficiency in Infrastructure More ❯

scalable data pipelines and infrastructure using AWS (Glue, Athena, Redshift, Kinesis, Step Functions, Lake Formation). Utilise PySpark for distributed data processing, ETL, SQL querying, and real-time data streaming. Architect and implement robust data solutions for analytics, reporting, machine learning, and data science initiatives. Establish and enforce … including Glue, Athena, Redshift, Kinesis, Step Functions, and Lake Formation. Strong programming skills in Python and PySpark for data processing and automation. Extensive SQL experience (Spark-SQL, MySQL, Presto SQL) and familiarity with NoSQL databases (DynamoDB, MongoDB, etc.). Proficiency in Infrastructure More ❯

align with business needs and industry standards. The ideal candidate will have expertise in Java, SQL, Python, and Spark (PySpark & SparkSQL) while also being comfortable working with Microsoft Power Platform. Experience with Microsoft Purview is a plus. The role requires strong communication skills to collaborate effectively … 1. Data Architecture & Engineering Design and implement scalable data architectures that align with business objectives. Work with Java, SQL, Python, PySpark, and SparkSQL to build robust data pipelines. Develop and maintain data models tailored to organizational needs. Reverse-engineer data models from existing live systems. Utilize Microsoft Power … solutions with business goals. Analyze and mitigate the impact of data standard breaches. Required Skills & Qualifications: Strong proficiency in Java, SQL, Python, SparkSQL, and PySpark. Experience with Microsoft Power Platform (PowerApps, Power Automate, etc.). Good understanding of data governance, metadata management, and compliance frameworks. Ability to communicate More ❯

Experience with data modeling, warehousing, and building ETL pipelines. Proficiency in query languages such as SQL, PL/SQL, HiveQL, SparkSQL, or Scala. Experience with scripting languages like Python or KornShell. Knowledge of writing and optimizing SQL queries for large-scale, complex datasets. Experience … with big data technologies such as Hadoop, Hive, Spark, EMR. Experience with ETL tools like Informatica, ODI, SSIS, BODI, or DataStage. Our inclusive culture empowers Amazon employees to deliver the best results for our customers. If you have a disability and need workplace accommodations during the application and More ❯

Azure Databricks, Azure Data Factory, Delta Lake, Azure Data Lake (ADLS), Power BI. Solid hands-on experience with Azure Databricks - Pyspark coding and Spark SQL coding - Must have. Very good knowledge of data warehousing skills including dimensional modeling, slowly changing dimension patterns, and time travel. Experience More ❯

Implementation experience with AWS services - Hands on experience leading large-scale global data warehousing and analytics projects. - Experience using some of the following: Apache Spark/Hadoop ,Flume, Kinesis, Kafka, Oozie, Hue, Zookeeper, Ranger, Elasticsearch, Avro, Hive, Pig, Impala, Spark SQL, Presto, PostgreSQL, Amazon More ❯

engineers to supplement existing team during implementation phase of new data platform. Main Duties and Responsibilities: Write clean and testable code using PySpark and SparkSQL scripting languages, to enable our customer data products and business applications. Build and manage data pipelines and notebooks, deploying code in a structured, trackable and More ❯

batch mechanism. Good data modeling skills with knowledge of various industry standards such as dimensional modeling, star schemas etc. Proficient in writing performant SQL working with large data volumes. Experience designing and operating very large Data Warehouses. Experience with scripting for automation (e.g., UNIX Shell scripting, Python). … warehousing and building ETL pipelines - Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting languages (e.g., Python, KornShell) PREFERRED QUALIFICATIONS - Experience with big data technologies such as: Hadoop, Hive, Spark More ❯

availability and accessibility. Experience & Skills : Strong experience in data engineering. At least some commercial hands-on experience with Azure data services (e.g., Apache Spark, Azure Data Factory, Synapse Analytics). Proven experience in leading and managing a team of data engineers. Proficiency in programming languages such as PySpark … Python (with Pandas if no PySpark), T-SQL, and SparkSQL. Strong understanding of data modeling, ETL processes, and data warehousing concepts. Knowledge of CI/CD pipelines and version control (e.g., Git). Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Ability to manage multiple More ❯

availability and accessibility. Experience & Skills : Strong experience in data engineering. At least some commercial hands-on experience with Azure data services (e.g., Apache Spark, Azure Data Factory, Synapse Analytics). Proven experience in leading and managing a team of data engineers. Proficiency in programming languages such as PySpark … Python (with Pandas if no PySpark), T-SQL, and SparkSQL. Strong understanding of data modeling, ETL processes, and data warehousing concepts. Knowledge of CI/CD pipelines and version control (e.g., Git). Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Ability to manage multiple More ❯

availability and accessibility. Experience & Skills : Strong experience in data engineering. At least some commercial hands-on experience with Azure data services (e.g., Apache Spark, Azure Data Factory, Synapse Analytics). Proven experience in leading and managing a team of data engineers. Proficiency in programming languages such as PySpark … Python (with Pandas if no PySpark), T-SQL, and SparkSQL. Strong understanding of data modeling, ETL processes, and data warehousing concepts. Knowledge of CI/CD pipelines and version control (e.g., Git). Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Ability to manage multiple More ❯

warehousing and building ETL pipelines. Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala). Experience with one or more scripting language (e.g., Python, KornShell). PREFERRED QUALIFICATIONS Experience with big data technologies such as: Hadoop, Hive, Spark More ❯

transforming, and loading (ETL) large datasets from diverse sources. Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL, AWS - Redshift, and OLAP technologies, Model data and metadata for ad hoc and pre-built reporting. Work with product tech teams and build robust … and scalable data integration (ETL) pipelines using SQL, Python and Spark. Monitor and improve data pipeline performance, ensuring low latency and high availability. Automate repetitive data engineering tasks to streamline workflows and improve efficiency. About the team Supply Chain Optimization Technologies (SCOT) is the name of a complex … warehousing and building ETL pipelines Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) Experience with one or more scripting language (e.g., Python, KornShell) PREFERRED QUALIFICATIONS Experience with big data technologies such as: Hadoop, Hive, Spark More ❯

deliver accurate and timely data and reporting to meet or exceed SLAs Minimum Requirements: - 4+ years of data engineering experience - 4+ years of SQL experience - Experience with data modeling … warehousing, and building ETL pipelines - Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting languages (e.g., Python, KornShell) - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and More ❯

scale, high-volume, high-performance data structures for analytics and Reporting. Implement data structures using best practices in data modeling, ETL processes, and SQL, AWS - Redshift, and OLAP technologies, Model data and metadata for ad hoc and pre-built reporting. Work with product tech teams and build robust … and scalable data integration (ETL) pipelines using SQL, Python and Spark. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers. Interface with business customers, gathering requirements and delivering complete reporting solutions. Collaborate with Analysts, Business Intelligence Engineers, SDEs, and Product Managers to … warehousing and building ETL pipelines Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) Experience with one or more scripting languages (e.g., Python, KornShell) PREFERRED QUALIFICATIONS Bachelor's degree Our inclusive culture empowers Amazonians to deliver the best More ❯

Your qualifications and experience You are a pro at using SQL for data manipulation (at least one of PostgreSQL, MSSQL, Google BigQuery, SparkSQL) Modelling & Statistical Analysis experience, ideally customer related Coding skills in at least one of Python, R, Scala, C, Java or JS Track record of using … in one or more programming languages. Keen interest in some of the following areas: Big Data Analytics (e.g. Google BigQuery/BigTable, Apache Spark), Parallel Computing (e.g. Apache Spark, Kubernetes, Databricks), Cloud Engineering (AWS, GCP, Azure), Spatial Query Optimisation, Data Storytelling with (Jupyter) Notebooks, Graph Computing More ❯

Your qualifications and experience You are a pro at using SQL for data manipulation (at least one of PostgreSQL, MSSQL, Google BigQuery, SparkSQL) Modelling & Statistical Analysis experience, ideally customer related Coding skills in at least one of Python, R, Scala, C, Java or JS Track record of using … in one or more programming languages. Keen interest in some of the following areas: Big Data Analytics (e.g. Google BigQuery/BigTable, Apache Spark), Parallel Computing (e.g. Apache Spark, Kubernetes, Databricks), Cloud Engineering (AWS, GCP, Azure), Spatial Query Optimisation, Data Storytelling with (Jupyter) Notebooks, Graph Computing More ❯

Your qualifications and experience You are a pro at using SQL for data manipulation (at least one of PostgreSQL, MSSQL, Google BigQuery, SparkSQL). Modelling & Statistical Analysis experience, ideally customer related. Coding skills in at least one of Python, R, Scala, C, Java or JS. Track record of … in one or more programming languages. Keen interest in some of the following areas: Big Data Analytics (e.g. Google BigQuery/BigTable, Apache Spark), Parallel Computing (e.g. Apache Spark, Kubernetes, Databricks), Cloud Engineering (AWS, GCP, Azure), Spatial Query Optimisation, Data Storytelling with (Jupyter) Notebooks, Graph Computing More ❯