401 to 425 of 773 Azure Synapse Analytics Jobs

building production-grade AI solutions, and embedding best practices in data and AI engineering. Key Responsibilities: Lead the design and delivery of scalable data architectures and pipelines to meet analytics and AI needs. Develop and maintain AI and data products aligned to business outcomes. Champion automation-first engineering practices across ingestion, transformation, and deployment. Design and deploy generative and … predictive AI solutions using Azure and open-source frameworks. Implement modern DataOps and MLOps practices, including CI/CD pipelines and monitoring. Establish and maintain reusable enterprise data models and semantic layers for self-service analytics. Mentor and develop a high-performing engineering team. Collaborate with stakeholders to embed insight and AI in product delivery and business decision-making. … About You: Deep expertise in data engineering, data pipelines, and semantic models. Hands-on experience building data platforms on Microsoft Azure (Data Factory, Synapse, Databricks, Purview). Skilled in deploying machine learning models and generative AI applications in production. Strong programming skills in Python, SQL, YAML. Experience with CI/CD and infrastructure-as-code (e.g., Terraform/ More ❯

and participating in the design, development, testing, implementation, and maintenance of data-driven software solutions. The ideal candidate will possess expert-level knowledge of Python, C#, .NET, Databricks, and Azure, ensuring alignment with business objectives. They will identify and champion innovation in technology and processes to unlock new commercial opportunities. Collaborating closely with the trading team, the Senior Data … Engineer will shape quantitative strategies and ensure data/analytics pipelines meet front-office needs. This position requires the ability to work independently with minimal guidance, exercising broad latitude in decision-making. Key responsibilities include migrating an existing Python-based reporting/analytics application and its data workflows from Azure SQL to Databricks, creating and optimizing data … pipelines in Databricks, and leveraging scheduling, job orchestration, and optionally machine learning features to serve trading and analytics needs. The Senior Data Engineer will also collaborate with quantitative analysts, traders, and commercial stakeholders to design new application features, dashboards, and analytics for portfolio management, pricing, and risk analysis. Additionally, they will support broader IT initiatives by ensuring compliance More ❯

solutions that have the power to transform businesses so that they stay competitive and can continue to grow. Digital Strategy execution that makes companies more agile and flexible. Advanced Analytics that gives them insight into what happens now or in the nearby future by recognising specific patterns in their data. They build data heavy intelligent solutions which captures real … fight against cancer Utilise Chat GPT Build the latest products in computer vision & digital twins. Responsibilities for the Successful Data Engineer: Design and implement complex data engineering solutions using Azure technologies. Build scalable, reliable, and maintainable data pipelines to support big data processing and analytics. Drive technical excellence by helping to shape the architectural direction of data systems and … platforms. Ensure data quality, performance, and security while supporting clients in unlocking actionable insights from their data. The Successful Data Engineer will have: Extensive experience in Azure technologies , including Azure Data Factory, Azure Databricks, Azure Synapse, and other relevant tools. Strong proficiency in data engineering principles , with expertise in building scalable, performant, and maintainable data More ❯

ELT, data warehousing, data lake, data lakehouse, data governance, Big Data, AI/ML, reporting and data visualisation. Knowledge of IT infrastructure, networking, security and cloud technologies such as Azure (Azure integration and data Services, Azure Data Factory, Azure Synapse Analytics, Azure Databricks Collaborated with Data Engineers to define data integration and orchestration … manipulation. Identity and Access Management (IAM) Concepts: Understanding of directory services, identity lifecycle management, and privilege management. Familiarity with technologies like REST, SCIM, Active Directory, LDAP, and cloud platforms (Azure, AWS, GCP). Knowledge of automation tools and concepts for streamlining verification processes. Ability to create clear and effective visualizations to communicate data insights. Soft Skills: Strong written and More ❯

ELT, data warehousing, data lake, data lakehouse, data governance, Big Data, AI/ML, reporting and data visualisation. Knowledge of IT infrastructure, networking, security and cloud technologies such as Azure (Azure integration and data Services, Azure Data Factory, Azure Synapse Analytics, Azure Databricks Collaborated with Data Engineers to define data integration and orchestration … manipulation. Identity and Access Management (IAM) Concepts: Understanding of directory services, identity lifecycle management, and privilege management. Familiarity with technologies like REST, SCIM, Active Directory, LDAP, and cloud platforms (Azure, AWS, GCP). Knowledge of automation tools and concepts for streamlining verification processes. Ability to create clear and effective visualizations to communicate data insights. Soft Skills: Strong written and More ❯

who take initiative, embrace challenges, and think outside the box. As a Data Engineer, your mission would include: Designing, building, and maintaining robust data pipelines to support AI and analytics initiatives. Collaborating with stakeholders to understand business needs and ensure data is structured effectively for AI applications. Developing and optimizing SQL queries (especially T-SQL) and Python scripts for … efficient data processing. Implementing data modeling techniques to ensure scalable and maintainable data architectures. Working with cloud platforms such as Azure or AWS, leveraging tools like Databricks, Data Factory, and Synapse Analytics. Ensuring best practices in DevOps, version control, and data governance. Managing orchestration workflows using Airflow or similar tools. Supporting AI teams by preparing high-quality, structured … least 3 years of experience in Data Engineering. Experience in client-facing roles, in consulting companies. Technical Skills: Strong expertise in SQL (especially T-SQL) and Python. Experience in Azure with tools like Databricks, Data Factory, and Synapse Analytics. Knowledge of data modeling techniques. Familiarity with DevOps and version control best practices. Experience with Airflow or other orchestration More ❯

Computer Science 5+ years of experience in architecting and delivering integrated data solutions 3+ years of experience building and optimizing data pipelines in cloud/hybrid cloud computing environments (Azure, Google Cloud). Expertise in data management, information integration and analytics practices and capabilities. Experience working with modern data architectures and engineering methodologies (Domain driven data architecture, Scalable … you a competitive edge (preferred qualifications): Proven track record in leading and delivering on complex data projects Exposure to projects supporting development of data pipelines and data products using Azure storage, search, catalog, API management, and data processing & analytics services such as Azure Data Factory, Data Bricks, Synapse, and PowerBI. Appreciation of application architecture principles and More ❯

Computer Science* 5+ years of experience in architecting and delivering integrated data solutions* 3+ years of experience building and optimizing data pipelines in cloud/hybrid cloud computing environments (Azure, Google Cloud).* Expertise in data management, information integration and analytics practices and capabilities.* Experience working with modern data architectures and engineering methodologies (Domain driven data architecture, Scalable … you a competitive edge (preferred qualifications):* Proven track record in leading and delivering on complex data projects* Exposure to projects supporting development of data pipelines and data products using Azure storage, search, catalog, API management, and data processing & analytics services such as Azure Data Factory, Data Bricks, Synapse, and PowerBI.* Appreciation of application architecture principles and More ❯

The Data Engineer at AllPoints Fibre will join our Data and Analytics team. Reporting to the Director of Data and Analytics, you will play a pivotal role in our data transformation. AllPoints Fibre is on a transformative journey to become the most recommended way to connect in the UK telecoms market. At the core of this initiative is … but also drive significant commercial and strategic insights via advanced analytics. This role would suit an experienced data professional who has previously built data infrastructure around the Microsoft Fabric analytics platform. The role will require you to work closely with stakeholders across our business to deliver reliable data in appropriate format for reporting needs. Role overview: Data engineers at … Collaboration in a transient team environment Adaptability to frequently changing priorities Working with DataLake/Lakehouse/Warehouse paradigms and associated data models. Expert knowledge of the Microsoft Fabric Analytics Platform (Azure SQL, Synapse, PowerBI) Use of Python for data engineering tasks, including data ingestion from APIs, creation and management of parquet files, execution of ML models. More ❯

on our vision which is to empower every colleague and client of BDO with data. You will be working as part of a multi-disciplinary team of data and analytics managers, data analysts and fellow data engineers to develop and manage data products that can empower our people to make decisions from data to drive growth activities and bring … to meet our data product and business requirements You'll be someone with: Experience and expertise in using SQL and Python and are comfortable using them everyday Experience in Azure technologies, particularly SQL DB, Azure Synapse, Data Factory, Azure Data Bricks and PowerBI Experience in processing data from flat files, databases, APIs, data streams and using More ❯

ownership of the end-to-end management of Pret’s SQL databases and cloud-based Snowflake platform, enabling the business to efficiently store, manage, and access critical data for analytics, reporting, and operations. Reporting to the Lead Data Engineer, you will collaborate closely with the Data Engineering team and business stakeholders to optimise database performance, troubleshoot issues, and ensure … of Pret’s MSSQL Server and Snowflake environments, ensuring high performance, reliability, and scalability. Design, implement, and optimise database architectures and data storage solutions to support data pipelines and analytics requirements. Monitor, troubleshoot, and resolve database performance issues, including query optimisation, indexing, and resource management. Collaborate with the Lead Data Engineer and Data Engineering team to build and maintain … Support the delivery of CI/CD pipelines, enabling automation and seamless deployments across SQL and Snowflake environments. Provide expertise in query optimisation and data modelling to support reporting, analytics, and application performance. Collaborate with stakeholders across Operations, Finance, HR, and IT to ensure database solutions align with business requirements and objectives. Stay up to date with emerging tools More ❯

services for use across all our business use cases. In this specialist role you'll work closely with both data delivery and data science teams to enable AWS and Azure environments as required by the various programmes. You'll support with the setup, maintenance and enhancement of data lab environments and the enablement of new tooling for data science … of data science and other cloud native functionality through dev to production environments What will your day look like? • Design and Deliver cloud based platforms on both AWS and Azure • Own and drive the enablement of data lab environment(s) for use in data science, enabling new tooling as required by the team • Management and promotion of data science … databases, ETL tooling, storage etc) • Collaborate with business and technical teams to agree services required and enable them with clear communications of status, and usage • Continuously explore new data analytics techniques and tools to improve efficiency and analytical capability within the team. What do we expect from you? • ML ops experience essential • Proficiency in SQL, and Python or similar More ❯

s needs by defining data schemas, optimizing data storage, and establishing data access controls and security measures. Defines and implements the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platforms. Designs and implements processes for the ETL process from various sources into the organization’s data systems. Translates high-level business requirements into data … project architectural artifacts across the EA group through governance forums. Defines and manages standards, guidelines, and processes to ensure data quality. Works with IT teams, business analysts, and data analytics teams to understand data consumers’ needs and develop solutions. Evaluates and recommends emerging technologies for data management, storage, and analytics. Skills and qualifications: At least five years of relevant … experience in design and implementation of data models for enterprise data initiatives Experience leading projects involving data modeling, data design, and data analysis. Design experience in Azure Fabric, Synapse, and Power BI/Tableau Design experience in Informatica Customer 360 and Product 360 and Reference Data Management Strong ability in programming languages Ability in data science languages/ More ❯

s needs by defining data schemas, optimizing data storage, and establishing data access controls and security measures. Defines and implements the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platforms. Designs and implements processes for the ETL process from various sources into the organization’s data systems. Translates high-level business requirements into data … project architectural artifacts across the EA group through governance forums. Defines and manages standards, guidelines, and processes to ensure data quality. Works with IT teams, business analysts, and data analytics teams to understand data consumers’ needs and develop solutions. Evaluates and recommends emerging technologies for data management, storage, and analytics. Skills and qualifications: At least five years of relevant … experience in design and implementation of data models for enterprise data initiatives Experience leading projects involving data modeling, data design and data analysis. Design experience in Azure Fabric, Synapse, and Power BI/Tableau Design experience in Informatica Customer 360 and Product 360 and Reference Data Management Strong ability in programming languages Ability in data science languages/ More ❯

in growing data practices. Expertise in data architecture, data modelling, data analysis, and data migration. Strong knowledge of SQL, NoSQL, cloud-based databases (e.g., AWS Redshift, Snowflake, Google BigQuery, Azure Synapse). Experience in ETL development, data pipeline automation, and data integration strategies. Familiarity with AI-driven analytics Strong understanding of data governance, security, and regulatory compliance. More ❯

Responsibilities : 16-18+ years of total experience in DWBI, Big Data, Cloud Technologies Implementation experience and hands on experience in either of the 2 Cloud technologies – Azure, AWS, GCP, Snowflake, Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam … or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions, actively contribute to RfP response. Ability to be a SPOC for all technical discussions across industry … communication skills. A minimum of 5 years’ experience in a similar role. Ability to lead and mentor the architects. Required Skills : Mandatory Skills [at least 2 Hyperscalers]: GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF. Preferred Skills More ❯

Responsibilities : 16-18+ years of total experience in DWBI, Big Data, Cloud Technologies Implementation experience and hands on experience in either of the 2 Cloud technologies – Azure, AWS, GCP, Snowflake, Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam … or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions, actively contribute to RfP response. Ability to be a SPOC for all technical discussions across industry … communication skills. A minimum of 5 years’ experience in a similar role. Ability to lead and mentor the architects. Required Skills : Mandatory Skills [at least 2 Hyperscalers]: GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF. Preferred Skills More ❯

Responsibilities : 16-18+ years of total experience in DWBI, Big Data, Cloud Technologies Implementation experience and hands on experience in either of the 2 Cloud technologies – Azure, AWS, GCP, Snowflake, Databricks Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam … or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions, actively contribute to RfP response. Ability to be a SPOC for all technical discussions across industry … communication skills. A minimum of 5 years’ experience in a similar role. Ability to lead and mentor the architects. Required Skills : Mandatory Skills [at least 2 Hyperscalers]: GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF. Preferred Skills More ❯

optimisation) Strong SQL skills and/or programming knowledge in Python, Java, Scala, or .NET Experience with Git-based CI/CD tools (e.g. GitLab CI/CD, Jenkins, Azure DevOps) Clear and confident communicator in English Nice to Have Familiarity with Azure services like Data Factory, Data Lake, or Synapse Exposure to Apache Spark , Hadoop , or More ❯

shape technical standards. ?? What You'll Do: Lead end-to-end data migration projects from legacy systems to D365. Design, build, and assure robust migration pipelines using SSIS, KingswaySoft, Azure Data Factory, and more. Define best practices, mentor data engineers, and drive continuous improvement. Engage with stakeholders, lead workshops, and translate business needs into technical solutions. Champion the use … or other SaaS platforms. Experience with fault-tolerant ETL pipelines and data governance tools. ?? Bonus Points For: Experience migrating from platforms like Salesforce, Raisers Edge, Hubspot, etc. Familiarity with Azure Synapse, Power BI, Python (Jupyter), and Microsoft Purview. Azure Data certifications and a passion for innovation in data engineering. ?? The Offer: Starting Salary : £80,000+ per annum More ❯

low-carbon energy in the UK. As our Data Engineering Lead, you'll be responsible for designing and leading the development of a secure, scalable data platform on Microsoft Azure , helping turn complex construction data into actionable insight. You'll manage the full data lifecycle - from ingestion and transformation to warehousing and modelling - all while ensuring data quality, integrity … for live environments To succeed in this role, you'll bring a blend of strong technical expertise and people leadership. We're looking for someone with experience in: Microsoft Azure Data services (Data Factory, Databricks, Azure SQL, Synapse) SQL, NoSQL, and API-based data pipelines Agile methodologies such as SCRUM or Kanban Leading engineering teams in complex More ❯

shape technical standards. ?? What You'll Do: Lead end-to-end data migration projects from legacy systems to D365. Design, build, and assure robust migration pipelines using SSIS, KingswaySoft, Azure Data Factory, and more. Define best practices, mentor data engineers, and drive continuous improvement. Engage with stakeholders, lead workshops, and translate business needs into technical solutions. Champion the use … or other SaaS platforms. Experience with fault-tolerant ETL pipelines and data governance tools. ?? Bonus Points For: Experience migrating from platforms like Salesforce, Raisers Edge, Hubspot, etc. Familiarity with Azure Synapse, Power BI, Python (Jupyter), and Microsoft Purview. Azure Data certifications and a passion for innovation in data engineering. ?? The Offer: Starting Salary : £80,000+ per annum More ❯

lead transformative data projects and architect solutions that drive business impact. Responsibilities: Partner with clients to understand data challenges and craft solutions using Microsoft Fabric. Design data architectures integrating Azure Synapse, Data Factory, Databricks, and Power BI. Manage end-to-end solution delivery, ensuring performance and scalability. Develop data models and pipelines for real-time insights. Optimize systems More ❯

Document data lineage and recommend improvements for data ownership and stewardship. Qualifications Programming: Python, SQL, Scala, Java. Big Data: Apache Spark, Hadoop, Databricks, Snowflake, etc. Cloud: AWS (Glue, Redshift), Azure (Synapse, Data Factory, Fabric), GCP (BigQuery, Dataflow). Data Modelling & Storage: Relational (PostgreSQL, SQL Server), NoSQL (MongoDB, Cassandra), Dimensional modelling. DevOps & Automation: Docker, Kubernetes, Terraform, CI/CD More ❯

Select Which statement best describes your hands on responsibility for architecting and tuning cloud native data lake/warehouse solutions (e.g., AWS S3 + Glue/Redshift, GCP BigQuery, Azure Synapse)? Select What best reflects your experience building ETL/ELT workflows with Apache Airflow (or similar) and integrating them into containerised CI/CD pipelines (Docker, GitHub More ❯