1 to 25 of 113 Remote/Hybrid Amazon Redshift Jobs

have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (eg, S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise ...

have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise ...

have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise ...

Spark or Hadoop. Experience with ETL/orchestration tools like Airflow, Talend or Azure Data Factory. Understanding of data warehousing solutions (Snowflake, BigQuery, Redshift or similar). Good understanding of data governance, GDPR and modern security practices. Strong problem solving skills and the ability to work with technical ...

Spark or Hadoop. Experience with ETL/orchestration tools like Airflow, Talend or Azure Data Factory. Understanding of data warehousing solutions (Snowflake, BigQuery, Redshift or similar). Good understanding of data governance, GDPR and modern security practices. Strong problem solving skills and the ability to work with technical ...

Spark or Hadoop. Experience with ETL/orchestration tools like Airflow, Talend or Azure Data Factory. Understanding of data warehousing solutions (Snowflake, BigQuery, Redshift or similar). Good understanding of data governance, GDPR and modern security practices. Strong problem solving skills and the ability to work with technical ...

Spark or Hadoop. Experience with ETL/orchestration tools like Airflow, Talend or Azure Data Factory. Understanding of data warehousing solutions (Snowflake, BigQuery, Redshift or similar). Good understanding of data governance, GDPR and modern security practices. Strong problem solving skills and the ability to work with technical ...

data-driven decision-making within the company. What We’re Looking For Minimum 4 years of data engineering experience. Strong experience with AWS services (Redshift, Lambda, S3, Glue, Lake Formation). Expertise in ETL/ELT development, data warehouse design (Kimball, Lakehouse). Proficiency in Python, Apache Spark ...

experience with dbt or similar transformation frameworks Proficiency in Python for data manipulation and pipeline support Experience working with cloud data warehouses (Snowflake, BigQuery, Redshift, or similar) Solid understanding of data warehousing concepts and modern ELT workflows Comfortable owning production data and supporting it end to end Strong communication ...

experience with dbt or similar transformation frameworks Proficiency in Python for data manipulation and pipeline support Experience working with cloud data warehouses (Snowflake, BigQuery, Redshift, or similar) Solid understanding of data warehousing concepts and modern ELT workflows Comfortable owning production data and supporting it end to end Strong communication ...

Classification policies. Maintain data dictionary. Maintain business level data model. Recommending and introducing new technology where needed. Core: Cloud data platforms (e.g. Snowflake, BigQuery, Redshift) Data transformation technology such as DBT Visual Studio Code Python CI automation systems such as Jenkins A git-based source control system such ...

Hands-on experience in data integration , including designing and optimising data pipelines (batch and streaming) and integrating cloud-based platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery ) with legacy systems, ensuring performance and scalability. Deep knowledge of ETL/ELT processes , leveraging tools like Apache Airflow, dbt, or Informatica ...

reconciliation checks Strong error handling, monitoring, and retry strategies in production pipelines Experience with incremental data processing patterns (CDC, watermarking, upserts) AWS Data Services Amazon S3: data lake architectures, partitioning strategies, lifecycle policies DynamoDB: data modeling, secondary indexes, streams, and performance optimization Amazon Redshift: foundational querying, integrations … performance considerations AWS Lambda for scalable data processing and orchestration Amazon EventBridge for event-driven and decoupled data pipelines Vector Databases & Embeddings Strong understanding of vector database concepts, indexing strategies, and performance trade-offs Design and implementation of embedding generation pipelines Optimization techniques for semantic search and retrieval accuracy ...

reconciliation checks Strong error handling, monitoring, and retry strategies in production pipelines Experience with incremental data processing patterns (CDC, watermarking, upserts) AWS Data Services Amazon S3: data lake architectures, partitioning strategies, lifecycle policies DynamoDB: data modeling, secondary indexes, streams, and performance optimization Amazon Redshift: foundational querying, integrations … performance considerations AWS Lambda for scalable data processing and orchestration Amazon EventBridge for event-driven and decoupled data pipelines Vector Databases & Embeddings Strong understanding of vector database concepts, indexing strategies, and performance trade-offs Design and implementation of embedding generation pipelines Optimization techniques for semantic search and retrieval accuracy ...

approach to data delivery. Skills & Experience Needed Strong background in data engineering, especially within AWS environments. Hands-on experience with services such as S3, Redshift, and other AWS data ecosystem tools. Familiarity with modern data stack tools: Airflow, dbt, Airbyte (or similar). Proficient in building automated pipelines ...

approach to data delivery. Skills & Experience Needed Strong background in data engineering, especially within AWS environments. Hands-on experience with services such as S3, Redshift , and other AWS data ecosystem tools. Familiarity with modern data stack tools: Airflow, dbt, Airbyte (or similar). Proficient in building automated pipelines ...

approach to data delivery. Skills & Experience Needed Strong background in data engineering, especially within AWS environments. Hands-on experience with services such as S3, Redshift , and other AWS data ecosystem tools. Familiarity with modern data stack tools: Airflow, dbt, Airbyte (or similar). Proficient in building automated pipelines ...

managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like Airflow or Dagster Experience with MLOps tools such as MLflow, Weights and Biases or similar Awareness of data ...

managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like Airflow or Dagster Experience with MLOps tools such as MLflow, Weights and Biases or similar Awareness of data ...

management role Excellent knowledge of data modelling, warehousing concepts, and large-scale distributed systems Hands-on experience with cloud-based data tools (AWS Redshift, Glue, EMR or similar) Proficiency in Python and SQL Understanding of DevOps principles, including CI/CD and IaC (e.g. Terraform) Clear communication skills ...

contributing to internal projects. Expect live whiteboarding sessions, asynchronous collaboration, and diverse tech stacks across multiple sectors. Tech stack highlights: AWS services: EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB Languages: Java, Python, Scala, Spark, SQL Big data architecture and ETL pipelines What we’re looking for: Strong problem-solving ...

contributing to internal projects. Expect live whiteboarding sessions, asynchronous collaboration, and diverse tech stacks across multiple sectors. Tech stack highlights: AWS services: EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB Languages: Java, Python, Scala, Spark, SQL Big data architecture and ETL pipelines What we’re looking for: Strong problem-solving ...

optimized for performance, reliability, and maintainability. 🌳 AWS Expertise: Utilize AWS services for data storage, processing, and analytics. Leverage AWS technologies such as S3, Glue, Redshift, and others to build and maintain data solutions. Implement best practices for security and compliance in an AWS environment. 🌳 Python Programming: Demonstrate proficiency ...

optimized for performance, reliability, and maintainability. 🌳 AWS Expertise: Utilize AWS services for data storage, processing, and analytics. Leverage AWS technologies such as S3, Glue, Redshift, and others to build and maintain data solutions. Implement best practices for security and compliance in an AWS environment. 🌳 Python Programming: Demonstrate proficiency ...

bring: 5+ years of full-stack experience in JavaScript (Node.js/React) and Python. Strong cloud background, ideally AWS (Lambda, S3, Glue, Redshift). Proven ability to design and deploy scalable web and data systems. Understanding of CI/CD, automated testing, and version control (Git). Experience integrating ...