{"id":43916,"url":"https://alion.io/job/barclays-data-engineer-etl-2","title":"Data Engineer - ETL","company":{"id":12541,"name":"Barclays","domain":"home.barclays","url":"https://alion.io/company/barclays-uk","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":94,"open_postings":205,"ghost_share":0.015,"stale_share":0.341,"repost_share":0.127,"time_to_fill_p50_days":17,"computed_at":"2026-10-28T05:59:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":17000,"max_usd":47000,"period":"year","method":"role_country_seniority_unknown","sample_n":171},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Databricks","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"IAM","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-08-05T00:00:00Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-28T00:43:45Z","board_verified":true,"closed_at":null,"days_open":84,"trust":{"level":"ok","repost_count":2,"flags":["repost"],"days_open":84},"description":"Job Description\nPurpose of the role\nTo 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.\nAccountabilities\nBuild and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.\nDesign and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.\nDevelopment of processing and analysis algorithms fit for the intended data complexity and volumes.\nCollaboration with data scientist to build and deploy machine learning models.\nAssistant Vice President Expectations\nTo advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.\nLead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes\nIf 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.\nOR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.\nConsult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.\nIdentify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.\nTake ownership for managing risk and strengthening controls in relation to the work done.\nPerform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.\nCollaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.\nEngage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.\nCommunicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.\nInfluence or convince stakeholders to achieve outcomes.\nAll 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.\nJoin us as a Data Engineer - ETL at Barclays, responsible for supporting the successful delivery of location strategy projects to plan, budget, agreed quality and governance standards. You will be invoved in design, develop, and deliver scalable data solutions. The successful candidate will be responsible for building robust data pipelines, enabling data processing and supporting large-scale data transformation initiatives across the organisation. This role requires strong expertise in PySpark, AWS cloud technologies, data engineering practices and modern data platform architectures. The candidate will collaborate with business stakeholders, architects, product owners and engineering teams to deliver secure, reliable and performant data products.\nTo be successful as a Data Engineer - ETL you should have experience with:\nDesign, develop and maintain scalable data pipelines using PySpark.\nBuild and optimise ETL/ELT solutions supporting large-scale enterprise data processing requirements.\nDevelop reusable frameworks, components and standards to accelerate data onboarding and analytics delivery.\nImplement data quality controls, validation frameworks and reconciliation processes.\nDeliver high-quality code following engineering best practices, coding standards and automated testing approaches.\nSome other highly valued skills may include:\nExcellent programming skills in Python/Pyspark.\nHands-on experience with Databricks and/or Snowflake.\nStrong experience with AWS Cloud services including S3, Glue, EMR, Lambda, EC2, DynamoDB, IAM, CloudWatch and CloudTrail.\nHands-on experience developing and optimising AWS Glue ETL jobs using PySpark.\nExperience with large-scale distributed data processing.\nSolid understanding of Data Lake, Lakehouse and Modern Data Platform architectures.\nExpertise with Git-based source control platforms.\nExperience in Airflow.\nYou 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.\nThis role is based out of Bengaluru.","description_format":"text","description_chars":5605,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Cards & Card 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