51 to 75 of 503 Apache Jobs in London

ad hoc to scalable, production-grade systems - Collaborate closely with senior stakeholders and shape the future of the data platform - Python | SQL | Snowflake | AWS (S3, Docker, Terraform) | Airflow | DBT | Apache Spark & Iceberg | PostgresDB The ideal candidate: - 5+ years as a senior/principal data engineer - Experience leading or mentoring engineers - Strong technical grounding - Start-up/scale-up mindset More ❯

work for the biggest multinational companies where years-long behemoth projects are the norm, our projects are fast-paced, typically 2 to 4 months long. Most are delivered using Apache Spark/Databricks on AWS/Azure and require you to directly manage the customer relationship alone or in collaboration with a Project Manager. Additionally, at this seniority level … no shortage of learning opportunities at DATAPAO, meaning that you'll get access to Databricks' public and internal courses to learn all the tricks of Distributed Data Processing, MLOps, Apache Spark, Databricks, and Cloud Migration from the best. Additionally, we'll pay for various data & cloud certifications, you'll get dedicated time for learning during work hours, and access … 100.000 GBP/year , depending on your assessed seniority level during the selection process. @ DATAPAO we are delivery partners and the preferred training provider for Databricks, the creators of Apache Spark. Additionally, we are Microsoft Gold Partners in delivering cloud migration and data architecture on Azure. Our delivery partnerships enable us to work in a wide range of industries More ❯

focus on automation and data process improvement. Demonstrated experience in designing and implementing automation frameworks and solutions for data pipelines and transformations. Strong understanding of data processing frameworks (e.g., Apache Spark, Apache Kafka) and database technologies (e.g., SQL, NoSQL). Expertise in programming languages relevant to data engineering (e.g., Python, SQL). Hands on data preparation activities using More ❯

Familiarity with CI/CD pipelines for development workflows. Excellent analytical, problem-solving, and communication skills. Exposure to domain-specific languages such as Slang. Experience with orchestration tools like Apache Airflow or dbt. Understanding of data governance and compliance standards. Ability to work collaboratively in agile, fast-paced environments. About Capgemini Capgemini is a global business and technology transformation More ❯

retail, infrastructure and telco. The ideal candidate with have expertise in some of the following: Python, SQL, Scala, and Java for data engineering. Strong experience with big data tools (Apache Spark, Hadoop, Databricks, Dask) and cloud platforms (AWS, Azure, GCP). Proficient in data modelling (relational, NoSQL, dimensional) and DevOps automation (Docker, Kubernetes, Terraform, CI/CD). Skilled More ❯

products or platforms Strong knowledge of SQL and experience with large-scale relational and/or NoSQL databases Experience testing data pipelines (ETL/ELT), preferably with tools like Apache Airflow, dbt, Spark, or similar Proficiency in Python or similar scripting language for test automation Experience with cloud platforms (AWS, GCP, or Azure), especially in data-related services Familiarity More ❯

products or platforms Strong knowledge of SQL and experience with large-scale relational and/or NoSQL databases Experience testing data pipelines (ETL/ELT), preferably with tools like Apache Airflow, dbt, Spark, or similar Proficiency in Python or similar scripting language for test automation Experience with cloud platforms (AWS, GCP, or Azure), especially in data-related services Familiarity More ❯

skills in Python, Java, Scala, or a similar language. Proficiency in database technologies (SQL, NoSQL, time-series databases) and data modelling. Strong understanding of data pipeline orchestration tools (e.g., Apache Airflow, Kubernetes). You thrive when working as part of a team. Comfortable in a fast-paced environment. Have excellent written and verbal English skills. Last but not least More ❯

. Strong understanding of data security, quality, and governance principles. Excellent communication and collaboration skills across technical and non-technical teams. Bonus Points For: Experience with orchestration tools like Apache Airflow. Familiarity with real-time data processing and event-driven systems. Knowledge of observability and anomaly detection in production environments. Exposure to visualization tools like Tableau or Looker. Relevant More ❯

Foundations: Data Warehousing: Knowledge of tools like Snowflake, DataBricks, ClickHouse and traditional platforms like PostgreSQL or SQL Server. ETL/ELT Development: Expertise in building pipelines using tools like Apache Airflow, dbt, Dagster. Cloud providers: Proficiency in Microsoft Azure or AWS. Programming and Scripting: Programming Languages: Strong skills in Python and SQL. Data Modeling and Query Optimization: Data Modeling More ❯

models in close cooperation with our data science team Experiment in your domain to improve precision, recall, or cost savings Requirements Expert skills in Java or Python Experience with Apache Spark or PySpark Experience writing software for the cloud (AWS or GCP) Speaking and writing in English enables you to take part in day-to-day conversations in the More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

integrating Monitoring Tools (Datadog/Kibana/Grafana/Prometheus). 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. Writing and analysing SQL queries. Application overVIOOH Our recruitment team will work hard to give you a positive experience More ❯

What would be advantageous: Strong understanding of financial markets. Experienceworking with hierarchical referencedata models. Provenexpertise in handling high-throughput, real-time marketdata streams Familiarity with distributed computing frameworks suchas Apache Spark Operational experience supporting real time systems. Equal Opportunity Workplace We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national More ❯

data into a data platform using Fivetran. Experience of developing BI dashboards using Power BI. Knowledge of security concepts relevant to Azure. Experience of workflow management tools such as Apache Airflow. Interested in the role? Complete the online application. We look forward to getting to know you. Discover more about LGT Wealth Management A message from our CEO Ben More ❯

Python, or C# with Spring Boot or .NET Core. Data Platforms: Warehouses: Snowflake, Google BigQuery, or Amazon Redshift. Analytics: Tableau, Power BI, or Looker for client reporting. Big Data: Apache Spark or Hadoop for large-scale processing. AI/ML: TensorFlow or Databricks for predictive analytics. Integration Technologies: API Management: Apigee, AWS API Gateway, or MuleSoft. Middleware: Red Hat More ❯

MySQL, PostgreSQL, or Oracle Experience with big data technologies such as Hadoop, Spark, or Hive Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow Proficiency in Python and at least one other programming language such as Java, or Scala Willingness to mentor more junior members of the team Strong analytical and problem More ❯

data ecosystem (e.g., Pandas, NumPy) and deep expertise in SQL for building robust data extraction, transformation, and analysis pipelines. Hands-on experience with big data processing frameworks such as Apache Spark, Databricks, or Snowflake, with a focus on scalability and performance optimization Familiarity with graph databases (e.g., Neo4j, Memgraph) or search platforms (e.g., Elasticsearch, OpenSearch) to support complex data More ❯

Proficiency in one or more programming languages including Java, Python, Scala or Golang. Experience with columnar, analytical cloud data warehouses (e.g., BigQuery, Snowflake, Redshift) and data processing frameworks like Apache Spark is essential. Experience with cloud platforms like AWS, Azure, or Google Cloud. Strong proficiency in designing, developing, and deploying microservices architecture, with a deep understanding of inter-service More ❯

field. Technical Skills Required · Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). · Experience with Apache Spark or any other distributed data programming frameworks. · Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. · Experience with cloud infrastructure like AWS or More ❯

on platforms such as AWS, Azure, GCP, and Snowflake. Understanding of cloud platform infrastructure and its impact on data architecture. 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 More ❯

on platforms such as AWS, Azure, GCP, and Snowflake. Understanding of cloud platform infrastructure and its impact on data architecture. 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 More ❯

exploring new technologies and methodologies to solve complex data challenges. Proven experience leading data engineering projects or teams. Expertise in designing and building data pipelines using frameworks such as Apache Spark, Kafka, Glue, or similar. Solid understanding of data modelling concepts and experience working with both structured and semi-structured data. Strong knowledge of public cloud services, especially AWS More ❯

might be more valuable than your direct technical contributions on a project. You care about your craft In addition it would be a bonus if you have Worked with Apache Airflow - we use Airflow extensively to orchestrate and schedule all of our data workflows. A good understanding of the quirks of operating Airflow at scale would be helpful. Experience More ❯

based languages is a plus. Data Warehousing: Hands-on experience with cloud-based data warehouses. Data Modeling: Proficiency in designing efficient database schemas. Workflow Orchestration: Familiarity with tools like Apache Airflow. Data Streaming: Experience with data streaming and Change Data Capture (CDC). Infrastructure: Proficiency in Terraform and GitHub Actions. Compliance: Experience in setting up PII anonymization and RBAC. More ❯