that address complex business requirements and drive decision-making. Your skills and experience Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR, Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS, and AWS Step Functions. Programming Skills: Strong experience … and Scala. Expertise in Data Storage Technologies: In-depth knowledge of Data Warehouse, Database technologies, and Big Data Eco-system technologies such as AWS Redshift, AWS RDS, and Hadoop. Experience with AWS Data Lakes: Proven experience working with AWS data lakes on AWS S3 to store and process both More ❯
Job ID: Amazon Web Services Korea LLC Are you a Data Analytics specialist? Do you have Data Engineering, Data Warehousing and Data Lake experience? Do you like to solve the most complex and high scale (billions + records) data challenges in the world today? Do you like to work … the newest data analytic technologies? Would you like a career path that enables you to progress with the rapid adoption of cloud computing? At Amazon Web Services (AWS), we're hiring highly technical data architects to collaborate with our customers and partners on key engagements. Our consultants will develop … pre-sales, training and support teams to help partners and customers learn and use AWS services such as Athena, Glue, Lambda, S3, DynamoDB, QuickSight, Amazon EMR and Amazon Redshift. Since this is a customer facing role, you might be required to travel to client locations and deliver professional More ❯
of experience in data engineering, with at least 2 years in a leadership or management role. Strong experience with data warehousing solutions (e.g., AWS Redshift, Google BigQuery, Snowflake). Expertise in data pipeline development, ETL tools, and frameworks (e.g., Apache Airflow, Talend, Fivetran). Proficiency in SQL and experience More ❯
of experience in data engineering, with at least 2 years in a leadership or management role. Strong experience with data warehousing solutions (e.g., AWS Redshift, Google BigQuery, Snowflake). Expertise in data pipeline development, ETL tools, and frameworks (e.g., Apache Airflow, Talend, Fivetran). Proficiency in SQL and experience More ❯
development, and implementation of complex data pipelines and ETL/ELT processes using cloud-native technologies (e.g. AWS Glue, AWS Lambda, AWS S3, AWS Redshift, AWS EMR). Troubleshoot and resolve complex data quality issues, performance bottlenecks, and production incidents. Develop and maintain CI/CD pipelines for data More ❯
Business Intelligence Engineer II, Amazon Grocery Data and Tech At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We are looking for a Business Intelligence Engineer in the Amazon Grocery Data … multiple analytical solutions. You will be responsible for delivering some of our most strategic analytics initiatives. You will create insights that support all of Amazon's grocery businesses and have a significant impact on Amazon's top-line and competitive position. A successful candidate will bring deep technical … rapidly deliver services that have a broad business impact. They will define metrics to measure business performance and drive efficiency improvements. About the team Amazon Grocery Data and Technology (GDT) team is the central data team for Amazon Grocery, consisting of engineering teams (BIEs/DEs/SDEs More ❯
Amazon Marketing team is working on a platform that will provide real-time insights of traffic, sales, deals, and engagement and is looking for a rock star data engineer to build this. At Amazon, understanding customer data is paramount to our success in making it Earth's most … measurably effective marketing organization. This cuts across all of the investments we do across various verticals of A.in, Prime, Fashion, Fresh, Pay, etc. At Amazon, you will be working in one of the world's largest and most complex data environments. You will be part of a team that … will work with the marketing, retail, finance, analytics, machine learning, and technology teams to provide real-time data processing solutions that give Amazon leadership, marketers, and PMs timely, flexible, and structured access to customer insights. The team will be responsible for building this platform end to end using the More ❯
throughput, scalable, resilient and secure data pipelines. Experience with the following AWS technologies: Glue jobs, Athena, S3, Step functions, Lambda, RDS (Aurora Postgres), DMS, Redshift, QuickSight, Kenesis Firehose. Expert knowledge of SQL. Hands on experience with Kafka. Hands on experience with Terraform. Hands on experience of Python with a More ❯
Experience working with a modern data analytics stack Excellent communication and stakeholder management skills Nice to have Familiarity with the AWS environment (S3, Athena, Redshift) Experience with Python (Airflow, dbt, pySpark, Pandas) Experience with Snowflake Experience with Thoughtspot Familiarity with the command line Some understanding of Kafka Master's More ❯
Amazon Selection and Catalog Systems (ASCS) builds the systems that host and run the comprehensive e-commerce product catalog. We power the online shopping experience for customers worldwide, enabling them to find, discover, and purchase anything they desire. Our scaled, distributed systems process hundreds of millions of updates across … key insight trends using statistical rigor to inform the larger team of business-impacting developments Retrieve and analyze data using a broad set of Amazon's data technologies and resources Earn the trust of customers and stakeholders by understanding their needs and solving problems with technology Work closely with … decision making Leading reporting and analytics initiatives to drive data-informed decision making Designing, developing, and maintaining ETL processes and data visualization dashboards using Amazon QuickSight Transforming complex business requirements into actionable analytics solutions Solving ambiguous analyses with less well-defined inputs and outputs, driving to the heart of More ❯
Business Intelligence Engineer, Amazon Last Mile Come help Amazon create cutting-edge data and science-driven technologies for delivering packages to the doorstep of our customers! The Last Mile Routing & Planning organization builds the software, algorithms, and tools that make the "magic" of home delivery happen: our flow … decisions needed to plan and execute safe, efficient, and frustration-free routes for drivers around the world. Our team supports deliveries (and pickups!) for Amazon Logistics, Prime Now, Amazon Flex, Amazon Fresh, Lockers, and other new initiatives. As part of the Last Mile Science & Technology organization, you … ll partner closely with Product Managers, Data Scientists, and Software Engineers to drive improvements in Amazon's Last Mile delivery network. You will leverage data and analytics to generate insights that accelerate the scale, efficiency, and quality of the routes we build for our drivers through our end-to More ❯
workflows. Strong analytic skills related to working with unstructured datasets. Engineering best practices and standards. Experience with data warehouse software (e.g. Snowflake, Google BigQuery, AmazonRedshift). Experience with data tools: Hadoop, Spark, Kafka, etc. Code versioning (Github integration and automation). Experience with scripting languages such as More ❯
platforms (AWS, GCP, Azure) and related tools (e.g., Kubernetes, Terraform, CloudFormation). Experience with modern data platforms, including data lakes, data warehouses (e.g., Snowflake, Redshift, BigQuery), and real-time data processing. Proficiency in data modeling, ETL/ELT pipelines, and data integration tools. Strong understanding of security, compliance, and More ❯
is critical for structuring data for analysis. Proficiency in cloud platforms, such as AWS and GCP, with hands-on experience in services like Databricks, Redshift, BigQuery, and Snowflake, is highly valued. Advanced Python skills for data manipulation, automation, and scripting, using libraries like Pandas and NumPy, are necessary for More ❯
e.g., Apache Spark, Airflow, dbt). Hands-on experience with cloud-based data solutions (e.g., AWS, GCP, Azure) and data warehouses (e.g., BigQuery, Snowflake, Redshift). In-depth knowledge of SEO metrics, search algorithms, and technical SEO principles. Experience working with APIs from Google Search Console, Google Analytics, SEMrush More ❯
data ingestion (both batch and streaming), CI/CD tooling (e.g. Azure DevOps, Terraform etc.) and interrogation with databases such as SQL Server, Oracle, Redshift etc. Experience developing solutions on any major cloud platform: Azure, AWS or GCP Experience with reporting tools such as Power BI, Tableau, Qlik etc. More ❯
data analysis, machine learning, and data visualization. In-depth knowledge of cloud platforms (AWS, Azure, Google Cloud) and related data services (e.g., S3, BigQuery, Redshift, Data Lakes). Expertise in SQL for querying large datasets and optimizing performance. Experience working with big data technologies such as Hadoop, Apache Spark More ❯
Data Platforms: Deep knowledge with at least one of the following database technologies and familiarity with the others: relational, columnar and NoSQL (e.g. Snowflake, Redshift, MySQL, Oracle, MongoDB, etc.). Expert SQL Strong Python: for automation, data manipulation, shell scripting experience and creation of custom applications. SDLC: Deep understanding More ❯
structured and unstructured data from multiple sources, ensuring efficient data ingestion, transformation, and storage. Develop and optimize data lake and data warehouse solutions using Amazon S3, Redshift, Athena, and Lake Formation. Implement data governance, security, and compliance best practices, including IAM roles, encryption, and access controls. Monitor and … focus on AWS cloud technologies. Proficiency in Python, PySpark, SQL, and AWS Glue for ETL development. Hands-on experience with AWS data services, including Redshift, Athena, Glue, EMR, and Kinesis. Strong knowledge of data modeling, warehousing, and schema design. Experience with event-driven architectures, streaming data, and real-time More ❯
. Strong analytic skills related to working with unstructured datasets. Engineering best practices and standards. Experience with data warehouse software (e.g. Snowflake, Google BigQuery, AmazonRedshift). Experience building and optimising pipelines and ETL/ELT workflows. Working knowledge of data warehouse technologies (Snowflake, BigQuery). Code versioning More ❯
City of London, Greater London, UK Hybrid / WFH Options
Delta Capita
in SQL, PL/SQL, and database management systems such as Oracle, SQL Server, MySQL, and PostgreSQL. Experience with data warehousing tools like Snowflake, Redshift, or BigQuery. Analytical Skills : Strong analytical and problem-solving skills, with the ability to analyse complex data requirements and develop effective solutions. Communication Skills More ❯
on experience working with visualization tools including ThoughtSpot, Power BI or Tableau. Familiarity with leading cloud-based data warehouses such as Azure, BigQuery, AWS Redshift, or Snowflake. Strong analytical and problem-solving abilities to address complex data challenges. Detail-oriented mindset with a focus on data accuracy and quality. More ❯
and unstructured data from diverse sources. Strong knowledge of SQL/NoSQL databases and cloud data warehouse technology such as Snowflake/Databricks/Redshift/BigQuery, including performance tuning and optimisation. Understanding of best practices for designing scalable and efficient data models, leveraging dbt for transformations. Familiarity with More ❯
CloudFormation Experience in Database optimization and management (especially for multi-tenant architectures) Extensive knowledge of AWS services, including EKS, Lambda, EC2, S3, RDS, Glue, Redshift, and ElastiCache Strong experience with GitOps workflows and tools, particularly ArgoCD Demonstrated expertise in CI/CD pipelines and automation Solid software engineering background More ❯
physical). Proficiency in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra). In-depth knowledge of data warehousing concepts and tools (e.g., Redshift, Snowflake, Google BigQuery). Experience with big data platforms (e.g., Hadoop, Spark, Kafka). Familiarity with cloud-based data platforms and services (e.g., AWS More ❯
