Herbert Smith Freehills Kramer
Senior Data Engineer
Salary
Competitive salary
Work type
Onsite
Level
mid
Category
Data Engineering
About the role
Herbert Smith Freehills Kramer is a world-leading global law firm, where our ambition is to help you achieve your goals.
Exceptional client service and the pursuit of excellence are at our core. We invest in and care about our client relationships, which is why so many are longstanding. We enjoy breaking new ground, as we have for over 170 years.
As a fully integrated transatlantic and transpacific firm, we are where you need us to be. Our footprint is extensive and committed across the world’s largest markets, key financial centres and major growth hubs.
At our best tackling complexity and navigating change, we work alongside you on demanding litigation, exacting regulatory work and complex public and private market transactions. We are recognised as leading in these areas.
We are immersed in the sectors and challenges that impact you. We are recognised as standing apart in energy, infrastructure and resources. And we’re focused on areas of growth that affect every business across the world.
All of this is achieved by supporting the growth of our people, who help us deliver on our ambition – which is to help you achieve yours.
Herbert Smith Freehills Kramer: Your goals. Our ambition
The Opportunity
Key Responsibilities
- Manage the capture, storage and dissemination the cloud infrastructure used by business in the data hub and other data management system
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Implementing data process that delivers
- Easy access to data domains for those who are enabled
- Data domain structures that enable self service and more rigorous analytics
- Data structures that optimise cost to serve the data
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure ‘big data’ technologies. (ETL & ELT)
- Design and build data models to enable analysts and data consumers to easily and quickly access needed data. This will be both structured and unstructured data.
- Build analytics technologies that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Proficiency in administering Azure databases, encompassing performance tuning, backup and recovery, and routine maintenance, ensuring optimal database functionality and reliability.
- Monitor access, and audit logs, and ensure data masking and encryption at rest and in transit. Adhering to strict security protocols.
- Understanding data quality frameworks and testing methodologies to validate data accuracy and reliability, and ensuring fit for purpose, trustworthy data for decision-making and reporting.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across global boundaries through multiple data centres and Azure regions.
- Design and development of Datalake and Deltalake technologies for cloud data ingestion, classification, storage and dissemination
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Work to manage data domains with data stewards to generate data products for consumption
- Work with metadata and metadata management tools, including reference data and master data management
- Proactively build the latest Azure enterprise data warehouse through to PowerBI reporting
- Back fill as the technical lead for the business intelligence/ data management team
- Manage the business intelligence team, until a manager is brought on board to fill that function
Qualifications, skills and experience
- 5+ years of experience in a Data Engineer role, with practical experience.
- Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organisational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Detailed experience in data modelling in cloud environments, structured and unstructured.
- Rostered on-call support for any issues with the Enterprise Data Warehouse (EDW cloud), Global Data Warehouse (GDW on premise), global ETL and data management (additional pay is provided for on-call activities).
- Certifications from Microsoft Azure would be highly considered. Microsoft Certified: Azure Data Engineer Associate. DP-203, no later that 12 months old
- Experience using the following software/tools:
- big data tools: Hadoop, Spark, Kafka, etc
- relational SQL and NoSQL databases
- with data pipeline and workflow management tools.
- Azure cloud services: and the Microsoft synapse technologies
- stream-processing systems: Storm, Spark-Streaming, etc.
- object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Microsoft stack as we are a Microsoft shop
- Demonstrated experience in cloud technologies:-
- Azure Data Factory
- Azure Synapse Analytics
- Azure Stream Analytics
- Azure Event Hubs
- Azure Data Lake Storage
- Azure Databricks
- PowerBI or similar data visualisation tool
- An innovative mindset, curious about AI and emerging technologies.
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Herbert Smith Freehills Kramer
Senior Data Engineer
Salary
Competitive salary
Work type
Onsite
Level
mid
Category
Data Engineering
About the role
Herbert Smith Freehills Kramer is a world-leading global law firm, where our ambition is to help you achieve your goals.
Exceptional client service and the pursuit of excellence are at our core. We invest in and care about our client relationships, which is why so many are longstanding. We enjoy breaking new ground, as we have for over 170 years.
As a fully integrated transatlantic and transpacific firm, we are where you need us to be. Our footprint is extensive and committed across the world’s largest markets, key financial centres and major growth hubs.
At our best tackling complexity and navigating change, we work alongside you on demanding litigation, exacting regulatory work and complex public and private market transactions. We are recognised as leading in these areas.
We are immersed in the sectors and challenges that impact you. We are recognised as standing apart in energy, infrastructure and resources. And we’re focused on areas of growth that affect every business across the world.
All of this is achieved by supporting the growth of our people, who help us deliver on our ambition – which is to help you achieve yours.
Herbert Smith Freehills Kramer: Your goals. Our ambition
The Opportunity
Key Responsibilities
- Manage the capture, storage and dissemination the cloud infrastructure used by business in the data hub and other data management system
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Implementing data process that delivers
- Easy access to data domains for those who are enabled
- Data domain structures that enable self service and more rigorous analytics
- Data structures that optimise cost to serve the data
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure ‘big data’ technologies. (ETL & ELT)
- Design and build data models to enable analysts and data consumers to easily and quickly access needed data. This will be both structured and unstructured data.
- Build analytics technologies that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Proficiency in administering Azure databases, encompassing performance tuning, backup and recovery, and routine maintenance, ensuring optimal database functionality and reliability.
- Monitor access, and audit logs, and ensure data masking and encryption at rest and in transit. Adhering to strict security protocols.
- Understanding data quality frameworks and testing methodologies to validate data accuracy and reliability, and ensuring fit for purpose, trustworthy data for decision-making and reporting.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across global boundaries through multiple data centres and Azure regions.
- Design and development of Datalake and Deltalake technologies for cloud data ingestion, classification, storage and dissemination
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Work to manage data domains with data stewards to generate data products for consumption
- Work with metadata and metadata management tools, including reference data and master data management
- Proactively build the latest Azure enterprise data warehouse through to PowerBI reporting
- Back fill as the technical lead for the business intelligence/ data management team
- Manage the business intelligence team, until a manager is brought on board to fill that function
Qualifications, skills and experience
- 5+ years of experience in a Data Engineer role, with practical experience.
- Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organisational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Detailed experience in data modelling in cloud environments, structured and unstructured.
- Rostered on-call support for any issues with the Enterprise Data Warehouse (EDW cloud), Global Data Warehouse (GDW on premise), global ETL and data management (additional pay is provided for on-call activities).
- Certifications from Microsoft Azure would be highly considered. Microsoft Certified: Azure Data Engineer Associate. DP-203, no later that 12 months old
- Experience using the following software/tools:
- big data tools: Hadoop, Spark, Kafka, etc
- relational SQL and NoSQL databases
- with data pipeline and workflow management tools.
- Azure cloud services: and the Microsoft synapse technologies
- stream-processing systems: Storm, Spark-Streaming, etc.
- object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Microsoft stack as we are a Microsoft shop
- Demonstrated experience in cloud technologies:-
- Azure Data Factory
- Azure Synapse Analytics
- Azure Stream Analytics
- Azure Event Hubs
- Azure Data Lake Storage
- Azure Databricks
- PowerBI or similar data visualisation tool
- An innovative mindset, curious about AI and emerging technologies.