Build and maintain data pipelines that transfer and process complete, consistent data
Design and implement data warehouses and data lakes that handle required volumes and security
Develop processing and analysis algorithms suited to data complexity and volume
Collaborate with data scientists to build and deploy machine learning models
From the employer’s posting
Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
Development of processing and analysis algorithms fit for the intended data complexity and volumes.
Collaboration with data scientist to build and deploy machine learning models.
Practical Ab Initio experience (GDE graphs, plans, psets, EME version management)
Python and PySpark, with DataFrames, RDDs and SparkSQL
SQL across DML, DDL and DCL, plus Oracle RDBMS
Linux/Unix and shell scripting
Experience working with MongoDB NoSQL database
Qualification wording
Practical Ab Initio experience (GDE graphs, plans, psets, EME object/version management, environment migration, object comparison/diff).
Experience in python and PySpark and strong knowledge on Dataframes, RDD and SparkSQL.
Experience in SQL in all 3 areas viz., DML (data manipulation language), DDL (data definition language) and DCL (data control language). Experience in working with Oracle RDBMS.
Proficiency in Linux/Unix and Shell scripting.
Experience in working with MongoDB NoSQL database.
Open 3 monthsWe first saw this posting 93 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
Status in our records
Live
First seen by us
Aug 13, 202693 days ago
Recorded sightings
230
Last seen by us
Nov 14, 2026
Employer says posted
Aug 10, 2026
Aug 13, 2026today
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 93
656
Up longer than most. Similar jobs usually come down between day 6 and day 56.
Well past Barclays’s usual: its jobs come down by about day 29.
From 13,745 similar postings that came down, and 322 of Barclays’s. Coming down is not always a hire.
Barclays is hiring
40 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
Shell
SQL
Ab Initio
AWS
MongoDB
NoSQL
Oracle
PySpark
Where the posting names them
- Proficiency in Linux/Unix and Shell scripting.
- Experience in python and PySpark and strong knowledge on Dataframes, RDD and SparkSQL.
- Experience in SQL in all 3 areas viz., DML (data manipulation language), DDL (data definition language) and DCL (data control language).
- Practical Ab Initio experience (GDE graphs, plans, psets, EME object/version management, environment migration, object comparison/diff).
- Proficiency in Linux/Unix and Shell scripting.
- Experience in python and PySpark and strong knowledge on Dataframes, RDD and SparkSQL.
- Experience in python and PySpark and strong knowledge on Dataframes, RDD and SparkSQL.
- Experience in SQL in all 3 areas viz., DML (data manipulation language), DDL (data definition language) and DCL (data control language).
- Experience in working with Oracle RDBMS.
To be successful as a Senior ETL Data Egg, you should have experience with:
- Practical Ab Initio experience (GDE graphs, plans, psets, EME object/version management, environment migration, object comparison/diff).
- Proficiency in Linux/Unix and Shell scripting.
- Experience in working with MongoDB NoSQL database.
- Exposure to cloud services like AWS.
- Experience in any kind of migration projects.
- Experience in working with Oracle RDBMS.
- Experience in working with MongoDB NoSQL database.
- Exposure to cloud services like AWS.
- Experience in SQL in all 3 areas viz., DML (data manipulation language), DDL (data definition language) and DCL (data control language).
- Experience in working with Oracle RDBMS.
- Experience in working with MongoDB NoSQL database.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 6 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 Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.
Accountabilities
Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
Development of processing and analysis algorithms fit for the intended data complexity and volumes.
Collaboration with data scientist to build and deploy machine learning models.
Analyst Expectations
To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
Requires in-depth technical knowledge and experience in their assigned area of expertise
Thorough understanding of the underlying principles and concepts within the area of expertise
They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate.
Will have an impact on the work of related teams within the area.
Partner with other functions and business areas.
Takes responsibility for end results of a team’s operational processing and activities.
Escalate breaches of policies / procedure appropriately.
Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.
Advise and influence decision making within own area of expertise.
Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function.
Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
Make evaluative judgements based on the analysis of factual information, paying attention to detail.
Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.
Guide and persuade team members and communicate complex / sensitive information.
Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
Join us as a Senior ETL Data Egg, at Barclays, where you will spearhead the evolution of our infrastructure and deployment pipelines, driving innovation and operational excellence. You will harness cutting-edge technology to build and manage robust, scalable and secure infrastructure, ensuring seamless delivery of our digital solutions.
To be successful as a Senior ETL Data Egg, you should have experience with:
Practical Ab Initio experience (GDE graphs, plans, psets, EME object/version management, environment migration, object comparison/diff).
Proficiency in Linux/Unix and Shell scripting.
Experience in python and PySpark and strong knowledge on Dataframes, RDD and SparkSQL.
Experience in SQL in all 3 areas viz., DML (data manipulation language), DDL (data definition language) and DCL (data control language).
Experience in working with Oracle RDBMS.
Experience in working with MongoDB NoSQL database.
Exposure to cloud services like AWS.
Experience in any kind of migration projects.
Some other highly valued skills may include:
Ability to engage with Stakeholders, elicit requirements/ user stories and translate requirements into ETL components.
Ability to understand the infrastructure setup and be able to provide solutions either individually or working with teams.
Good knowledge of Data Marts and Data Warehousing concepts.
Resource should possess good analytical and Interpersonal skills.
You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.