51 to 70 of 70 Remote Amazon Redshift Jobs

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

Strong problem-solving skills and ability to communicate insights to non-technical stakeholders. Experience working with large datasets and cloud-based data warehouses (BigQuery, Redshift, Snowflake). Familiarity with ETL processes and data pipeline optimization is a plus. Ability to work in a fast-paced, data-driven environment ...

with strong technical communication skills adaptable to diverse audiences. Nice-to-have: Experience with Snowflake or comparable cloud data warehouse solutions (e.g., Databricks, BigQuery, Redshift) Network/Security knowledge (e.g. SSO, SAML, VPCs, network policies, EntraID) Previous experience working in a central or shared data platform team Exposure ...

data warehousing concepts and implementation Deep knowledge of Kimball dimensional modelling methodology. Platforms & Tools Experience with Databricks (preferred) or similar platforms: Snowflake, BigQuery, Redshift, Synapse, or equivalent Strong proficiency with: SQL (advanced level) Spark/PySpark Data pipeline orchestration tools (e.g., Airflow, ADF, etc.) Data Modelling Extensive experience designing ...

cleared Location: London/Hybrid Duration: 5 months Essential Skills: Informatica Data project experience AWS Azure Desirable Skills: Hands-on expertise in AWS & Spark: Amazon EMR, S3, Lambda; strong PySpark/Python and SQL for large-scale batch processing. Data engineering at scale in government or similarly complex domains … expose data safely and reliably. Agile ways of working with Jira/Confluence; clear stakeholder communication and concise technical documentation. Data warehousing & modelling (e.g., Redshift; dimensional modelling). Basic Power BI familiarity to partner with BI developers and validate end-to-end data flows. AWS ecosystem depth (Athena, Redshift ...

core engineering workstream Produce clear documentation and BAU handover Profile The Data Engineer will have strong cloud data warehouse experience (BigQuery preferred; Snowflake/Redshift also considered) Proven experience integrating: CRM platforms ERP systems Billing/BSS solutions Experience delivering cutover + hypercare phases (essential) Ability to operate ...

with the following: *Palantir (FDP) *Python *PySpark *Exploratory Data Analysis *Data pipeline design/data engineering concepts *Dashboard/reporting dataset development *BI tools (Redshift, Databricks or similar) *Agile delivery environments If these technologies aren't clearly visible on your CV, you're unlikely to be shortlisted - so please ...

dimensional design Experience with cloud data warehouse platforms – Google BigQuery is the existing lakehouse technology; hands‐on experience with BigQuery or equivalent (Snowflake, Redshift, Databricks) is expected Ability to produce technology‐agnostic logical models and translate them into well‐reasoned implementation recommendations Proven ability to facilitate workshops with mixed ...

have a good knowledge of modern software engineering best practices, microservices, TDD/DDD, common Design Patterns Experience with Databricks, PostgreSQL, Amazon RedShift or MLflow would be great but not essential What's in it for you: As a Python Developer (Machine Learning AWS) you will earn ...

initiatives. Build scalable data integration and ingestion frameworks using AWS Glue, Step Functions, EventBridge and DMS. Design secure lakehouse and data warehouse solutions leveraging Amazon S3, AWS Lake Formation, Redshift and Athena. Enable AI and machine learning capabilities through governed, feature-ready datasets and integration with ...

looking for someone whose primary data platform experience is AWS, with deep hands-on knowledge across services such as S3, Glue, Kinesis, Redshift and EMR. As important as the technical delivery capability is the ability to think architecturally about data. They want someone who can articulate the reasoning behind … takes pride in seeing solutions through to production. Essential experience: AWS data stack ownership in a production environment (S3, Glue, Kinesis, Redshift, EMR) Strong data modelling background (dimensional modelling, CDM, LDM, star schema) ETL/ELT pipeline design and delivery across real-time and batch Data governance, security ...

through deployment and introduce modern engineering standards across the team. Key Responsibilities * Architect and develop applications using React, Node.js, Python and AWS (Lambda, S3, Redshift). * Integrate internal platforms with CRM and external partners via REST APIs. * Implement CI/CD, version control and testing frameworks to professionalise … Candidate Profile * 5 + years as a Full Stack Developer with expertise in React and Node.js. * Strong knowledge of AWS services (Lambda, S3, EC2, Redshift). * Experience building and consuming APIs and integrating applications with CRM or data systems. * Background in Agile software development and mentoring junior engineers. * Ability ...