151 to 175 of 952 Apache Jobs

to manage competing technical requirements across complex systems. Strong communication and stakeholder engagement skills, enabling you to translate technical solutions into business value. Desirable experience with tools like Snowflake, Apache Airflow, and AWS certification-or demonstrable equivalent knowledge-will help you thrive from day one. You'll benefit from Our compensation package includes a competitive salary, company bonus, holiday More ❯

and be the bridge between business goals and translating them to technical deliverables. What you'll do Build large-scale data pipelines using frameworks like Google Cloud Platform and Apache Beam. Work on projects powering new generative AI experiences and helping to build models. Learn and contribute to the team's best practices and techniques for building data pipelines More ❯

the development and adherence to data governance standards. Data-Driven Culture Champion : Advocate for the strategic use of data across the organization. Skills-wise, you'll definitely: Expertise in Apache Spark Advanced proficiency in Python and Pyspark Extensive experience with Databricks Advanced SQL knowledge Proven leadership abilities in data engineering Strong experience in building and managing CI/CD More ❯

solutions using Databricks on Azure or AWS. Databricks Components : Proficient in Delta Lake, Unity Catalog, MLflow, and other core Databricks tools. Programming & Query Languages : Strong skills in SQL and Apache Spark (Scala or Python). Relational Databases : Experience with on-premises and cloud-based SQL databases. Data Engineering Techniques : Skilled in Data Governance, Architecture, Data Modelling, ETL/ELT More ❯

English, problem-solving skills, attention to detail, ability to work remotely. Desirable: Cloud architecture certification (e.g., AWS Certified Solutions Architect). Experience with Drupal CMS, geospatial/mapping tools, Apache Airflow, serverless architectures, API gateways. Interest in conflict data, humanitarian tech, open data platforms; desire to grow into a solution architect or technical lead role. Application Process Submit CV More ❯

process. Data Governance Leadership : Drive the development and adherence to data governance standards. Data-Driven Culture Champion : Advocate for the strategic use of data across the organization. Expertise in Apache Spark Advanced proficiency in Python and Pyspark Extensive experience with Databricks Advanced SQL knowledge Strong experience in building and managing CI/CD pipelines. Experience in implementing data integrations More ❯

microservice architecture, API development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle management, including versioning More ❯

solutions using Databricks on Azure or AWS. Databricks Components : Proficient in Delta Lake, Unity Catalog, MLflow, and other core Databricks tools. Programming & Query Languages : Strong skills in SQL and Apache Spark (Scala or Python). Relational Databases : Experience with on-premises and cloud-based SQL databases. Data Engineering Techniques : Skilled in Data Governance, Architecture, Data Modelling, ETL/ELT More ❯

methodologies. Collaborating with stakeholders to define data strategies, implement data governance policies, and ensure data security and compliance. About you: Strong technical proficiency in data engineering technologies, such as Apache Airflow, ClickHouse, ETL tools, and SQL databases. Deep understanding of data modeling, ETL processes, data integration, and data warehousing concepts. Proficiency in programming languages commonly used in data engineering More ❯

driven performance analysis and optimizations. Strong communication skills and the ability to work in a team. Strong analytical and problem-solving skills. PREFERRED QUALIFICATIONS Experience with Kubernetes deployment architectures Apache NiFi experience Experience building trading controls within an investment bank ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and More ❯

applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Preferred qualifications, capabilities, and skills Familiarity with modern front-end technologies Familiarity with apache and tomcat-based applications. Exposure to cloud technologies and ansible Evolven exposure is a plus About Us J.P. Morgan is a global leader in financial services, providing strategic advice More ❯

Experience and qualifications Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proficiency in Core Tools: Cloud Run, Firestore, Apigee, Cloud Composer/Apache Airflow, Pub/Sub, Dataform (deincludbt), and Terraform (infrastructure as code). Familiarity with Google Cloud Services: AppEngine, Endpoints, BigQuery, Cloud Storage, Cloud Dataflow, and Cloud Datastore. Programming languages 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 ❯

Linux Understanding of data modelling/data warehouse/data archive/dashboards Experience with databases (e.g. Oracle, MongoDB, RDBMS, SQL) Experience with BI tools (e.g. Tableau) Knowledge of Apache (Kafka) Plus, attitude is key. We’re looking for someone adaptable and resilient, who’s invested in their growth and passionate about taking their career to the next level. More ❯

Bash, Ansible DevOps & CI/CD: Jenkins, GitLab CI/CD, Terraform Cloud & Infrastructure: AWS Testing & Quality: Cucumber, SonarQube Monitoring & Logging: ELK Stack (Elasticsearch, Logstash, Kibana), Grafana Dataflow & Integration: Apache NiFi Experience across multiple areas is desirable; we don't expect you to know everything but a willingness to learn and contribute across the stack is key. #LI-JS2 More ❯

tools to automate profit-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 More ❯

microservice architecture, API development. Machine Learning (ML): Deep understanding of machine learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing, feature engineering, and model evaluation. Knowledge of ML model deployment and serving strategies, including containerization and microservices. Familiarity with ML lifecycle management, including versioning More ❯

Proven desire to expand your cloud/platform engineering capabilities Experience working with Big Data Experience of data storage technologies: Delta Lake, Iceberg, Hudi Proven knowledge and understanding of Apache Spark, Databricks or Hadoop Ability to take business requirements and translate these into tech specifications Competence in evaluating and selecting development tools and technologies Sound like the role you More ❯

for data models, ETL processes, and BI solutions. Ensure data accuracy, integrity, and consistency across the data platform. Knowledge, Skills and Experience: Essentia l Strong expertise in Databricks and Apache Spark for data engineering and analytics. Proficient in SQL and Python/PySpark for data transformation and analysis. Experience in data lakehouse development and Delta Lake optimisation. Experience with More ❯

in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices 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 ❯

Azure cloud services across a mixture of Enterprise and SME environments Proficiency in Python, SQL, Azure Data Factory, Azure Synapse Analytics, Azure Data Lakes, and big data technologies like Apache Spark Experience with DevOps practices and CI/CD pipelines in an Azure environment is a plus. Certification in Azure (e.g., Microsoft Certified: Azure Data Engineer Associate) is highly More ❯

comprehensive documentation for data models, ETL processes, and BI solutions. Ensure data accuracy, integrity, and consistency across the data platform. Knowledge, Skills and Experience: Strong expertise in Databricks and Apache Spark for data engineering and analytics. Proficient in SQL and Python/PySpark for data transformation and analysis. Experience in data lakehouse development and Delta Lake optimisation. Experience with More ❯

microservice architecture, API development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle management, including versioning More ❯

networks into production Experience with Docker Experience with NLP and/or computer vision Exposure to cloud technologies (eg. AWS and Azure) Exposure to Big data technologies Exposure to Apache products eg. Hive, Spark, Hadoop, NiFi Programming experience in other languages This is not an exhaustive list, and we are keen to hear from you even if you don More ❯