Prior experience in IT consolidations, mergers, demergers and carve-outs
Strong observability experience: logs, metrics and traces
3 to 5 years with data lakes and warehouses on at least two vendors
Experience with at least two cloud providers (Azure and AWS)
Qualification wording
10+ years of relevant experience in data and analytics architecture
Prior experience in IT consolidations, mergers, demergers and carve-outs (mandatory)
Strong experience in observability: logs, metrics and traces for applications and infrastructure
3 to 5 years of working experience with data lakes and data warehouses, on at least two vendors
Experience with at least two cloud providers (Azure and AWS)
Tools in this posting
Python
SQL
AWS
Azure
Kafka
Power BI
Tableau
Airflow
Source — Tool mentions in context
Role Summary Designs the data, observability and analytics architecture for a carve-out. Owns the target-state data platform and the technical approach for separating and moving application, user and enterprise data. Builds new platforms from the ground up where the separated entity needs them. Job Responsibilities Design observability architecture covering logs, metrics and traces Define collection of application events and infrastructure events Design log ingestion, retention and analysis Design data pipelines and ETL for batch and streaming workloads Design data models and data lake, data warehouse and lakehouse architectures Design a greenfield data lake from the ground up Define ingestion and deduplication for structured and unstructured data Design the technical approach for application data and user data moves Design enterprise master data handling Design analytics, custom dashboards and reporting with Power BI or Tableau Define data security, access control, lineage and quality controls Produce high-level and low-level designs and review them with client architects Required Experience 10+ years of relevant experience in data and analytics architecture Strong experience in observability: logs, metrics and traces for applications and infrastructure Experience with log ingestion, retention and analysis at scale Experience building data pipelines, ETL and ELT Strong data modelling skills 3 to 5 years of working experience with data lakes and data warehouses, on at least two vendors Experience with data lakehouse architectures Experience handling structured and unstructured data Experience with batch processing and batch operations Experience with ingestion and deduplication Experience with data migration, including application data and user data Experience with enterprise master data management Experience building a greenfield data lake from the ground up Experience with at least two analytics tools, such as Power BI and Tableau, including custom dashboards Knowledge of data governance: cataloguing, lineage, quality, masking and access control Knowledge of orchestration and streaming tools such as Azure Data Factory, Airflow or Kafka Strong SQL skills and working knowledge of Python Experience with at least two cloud providers (Azure and AWS) Exposure to at least two OEMs or two vendors in each technology area Strong communication skills, with prior experience working with UK and EU clients Willingness to travel as required and to work in the client time zone Prior infrastructure background alongside the specialism above Prior experience in IT consolidations, mergers, demergers and carve-outs (mandatory) Relevant professional certifications strongly recommended
New Data Leadership postings at the employers we follow are up 7% over the last 5 weeks compared with the 5 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
US government figures for computer and information systems managers
Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Role Summary Designs the data, observability and analytics architecture for a carve-out. Owns the target-state data platform and the technical approach for separating and moving application, user and enterprise data. Builds new platforms from the ground up where the separated entity needs them. Job Responsibilities Design observability architecture covering logs, metrics and traces Define collection of application events and infrastructure events Design log ingestion, retention and analysis Design data pipelines and ETL for batch and streaming workloads Design data models and data lake, data warehouse and lakehouse architectures Design a greenfield data lake from the ground up Define ingestion and deduplication for structured and unstructured data Design the technical approach for application data and user data moves Design enterprise master data handling Design analytics, custom dashboards and reporting with Power BI or Tableau Define data security, access control, lineage and quality controls Produce high-level and low-level designs and review them with client architects Required Experience 10+ years of relevant experience in data and analytics architecture Strong experience in observability: logs, metrics and traces for applications and infrastructure Experience with log ingestion, retention and analysis at scale Experience building data pipelines, ETL and ELT Strong data modelling skills 3 to 5 years of working experience with data lakes and data warehouses, on at least two vendors Experience with data lakehouse architectures Experience handling structured and unstructured data Experience with batch processing and batch operations Experience with ingestion and deduplication Experience with data migration, including application data and user data Experience with enterprise master data management Experience building a greenfield data lake from the ground up Experience with at least two analytics tools, such as Power BI and Tableau, including custom dashboards Knowledge of data governance: cataloguing, lineage, quality, masking and access control Knowledge of orchestration and streaming tools such as Azure Data Factory, Airflow or Kafka Strong SQL skills and working knowledge of Python Experience with at least two cloud providers (Azure and AWS) Exposure to at least two OEMs or two vendors in each technology area Strong communication skills, with prior experience working with UK and EU clients Willingness to travel as required and to work in the client time zone Prior infrastructure background alongside the specialism above Prior experience in IT consolidations, mergers, demergers and carve-outs (mandatory) Relevant professional certifications strongly recommended