{"id":2171550,"url":"https://alion.io/job/barclays-cloud-data-engineer-4","title":"Cloud Data Engineer","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":96,"open_postings":214,"ghost_share":0.014,"stale_share":0.257,"repost_share":0.131,"time_to_fill_p50_days":14,"computed_at":"2026-10-09T06:01:00Z"}},"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":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"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":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Amazon CloudWatch","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"CloudFormation","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"DynamoDB","optional":true},{"name":"IAM","optional":true},{"name":"Spark","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-09T12:18:45Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-09T20:41:25Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"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.\nAnalyst Expectations\nTo perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.\nRequires in-depth technical knowledge and experience in their assigned area of expertise\nThorough understanding of the underlying principles and concepts within the area of expertise\nThey lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.\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 develop technical expertise in work area, acting as an advisor where appropriate.\nWill have an impact on the work of related teams within the area.\nPartner with other functions and business areas.\nTakes responsibility for end results of a team’s operational processing and activities.\nEscalate breaches of policies / procedure appropriately.\nTake responsibility for embedding new policies/ procedures adopted due to risk mitigation.\nAdvise and influence decision making within own area of expertise.\nTake 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.\nMaintain 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.\nDemonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.\nMake evaluative judgements based on the analysis of factual information, paying attention to detail.\nResolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.\nGuide and persuade team members and communicate complex / sensitive information.\nAct as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.\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.\nStep into the role of Cloud Data Engineer at Barclays, where you'll help shape and deliver our cloud-first data strategy. This role will design and build scalable AWS data platforms, analytics capabilities, and reusable data products. You will work in a collaborative engineering team to move trusted data from golden-source systems into governed cloud data layers and make it available for analytics and downstream consumption.\nYou may be assessed on key critical skills relevant for success in role such as:\nContribute to the cloud data strategy and translate business and analytical requirements into secure, scalable AWS data solutions.\nDesign, build, test, deploy, and support batch and event-driven data pipelines using AWS services such as AWS Glue, Step Functions, Lambda, Athena, S3, and EC2.\nUse enterprise hydration frameworks to ingest data from golden-source systems into governed source-aligned layers in the cloud.\nDevelop curated data models and reusable data products that are discoverable, trusted, and suitable for analytics, reporting, and downstream applications.\nDesign and implement data lake and data warehouse patterns, including appropriate partitioning, file formats, metadata, and performance optimization.\nDevelop robust transformation logic using SQL and Python or PySpark, with appropriate testing, reconciliation, and error handling.\nImplement workflow orchestration, scheduling, monitoring, alerting, restart, and recovery capabilities for production data pipelines.\nApply data quality, lineage, metadata, security, access-control, retention, and audit requirements throughout the data lifecycle.\nOptimize cloud data workloads for performance, reliability, scalability, and cost.\nCollaborate with data architects, platform engineers, source-system teams, analysts, product owners, and governance stakeholders.\nFollow engineering standards for source control, peer review, automated testing, CI/CD, documentation, and operational support.\nInvestigate production issues, perform root-cause analysis, and implement sustainable fixes and preventative controls.\nEssential Skills / Qualifications\nRelevant data engineering experience, including the design and delivery of production-grade data pipelines and analytical data platforms.\nStrong SQL skills and a solid understanding of data warehousing, dimensional modelling, data lake concepts, ETL/ELT patterns, and data lifecycle management.\nHands-on experience building cloud data solutions on AWS using AWS Glue, Step Functions, Lambda, Athena, S3, and EC2.\nProficiency in Python and/or PySpark for data processing, automation, and integration.\nExperience ingesting data from relational databases, files, APIs, and other enterprise sources into governed cloud data layers.\nExperience working with reusable ingestion or hydration frameworks and configurable, metadata-driven pipeline patterns.\nAbility to build curated data products from source-aligned data, including transformation, validation, reconciliation, and publication for consumers.\nKnowledge of data quality, metadata, lineage, security, encryption, identity and access management, monitoring, and audit controls.\nExperience with Git-based source control, automated testing, CI/CD, and deployment across development, test, and production environments.\nStrong analytical, troubleshooting, documentation, stakeholder-management, and written and verbal communication skills.\nDesirable / Good-to-Have Skills\nExperience with Databricks, including Apache Spark, Delta Lake, notebooks, workflows, and Unity Catalog.\nExperience with Astronomer or Apache Airflow for workflow orchestration and operational monitoring.\nKnowledge of AWS services such as Redshift, EMR, Lake Formation, Kinesis, DynamoDB, CloudWatch, IAM, and CloudFormation.\nExperience with infrastructure-as-code tools such as Terraform or CloudFormation.\nFamiliarity with data mesh or data-product principles, including ownership, discoverability, interoperability, and service-level expectations.\nExperience with data observability, schema evolution, data contracts, and cloud cost optimization.\nRelevant AWS or Databricks certification.\nExperience in banking or financial services and working within enterprise risk, security, and compliance frameworks.\nYou may be assessed on key essential 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 Pune.","description_format":"text","description_chars":7976,"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":["Professional development"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Cards & Card Issuing","Wealth Management & Financial Advisors","Investment Banking & M&A Advisory"],"lifecycle":[{"event":"open","at":"2026-10-09T12:18:45Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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