{"id":3563544,"url":"https://alion.io/job/job-mail-data-engineer-banking-cib","title":"Data Engineer – Banking (CIB)","company":{"id":701519,"name":"Job Mail","domain":"jobmail.co.za","url":"https://alion.io/company/job-mail","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":true,"listed_via":"jobmail.co.za","ats_vendor":"Schema","truth_index":null},"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":["Johannesburg, South Africa"],"countries":["ZA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":34000,"max_usd":76000,"period":"year","method":"role_country_seniority_unknown","sample_n":25},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EventBridge","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"FinOps","optional":true}],"status":"closed","first_seen_at":"2026-10-31T07:12:17Z","employer_posted_date":"2026-10-31","last_verified_at":"2026-11-02T20:16:10Z","board_verified":false,"closed_at":"2026-11-02T20:16:10Z","days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Company: BluePearl Consulting\nNumber of Vacancies: 1\nIndustry: Banking / Financial Services\nDepartment: Corporate and Investment Banking (CIB)\nContract Duration: 12 months, with potential extension up to 36 months\nExpected Start Date: 1 January 2027\nLocation: Rosebank, Johannesburg, Gauteng\nWork Arrangement: Hybrid - approximately 3 days onsite per week\nJob Summary\nBluePearl Consulting is seeking a strong, experienced Data Engineer to join a software and data engineering team within a Corporate and Investment Banking (CIB) environment.\nThe successful candidate will specialise in designing, developing and maintaining scalable data pipelines, data integration solutions and cloud-based data platforms. The role requires strong SQL and Python engineering skills, ETL/ELT expertise, data modelling capabilities and hands-on cloud data engineering experience, with AWS as the core platform.\nThe ideal candidate is a proactive self-starter who takes ownership of deliverables, solves problems independently and maintains high standards of data quality, security and engineering discipline.\nKey Responsibilities\nDesign, develop and maintain scalable ETL/ELT pipelines and data ingestion processes.\n\nWrite, optimise and troubleshoot advanced SQL queries, including CTEs and window functions.\n\nDevelop reusable Python modules, libraries and automated tests.\n\nBuild and maintain relational, dimensional and analytical data models.\n\nImplement data transformations, mappings, validation and reconciliation processes.\n\nDevelop and maintain data pipelines using AWS data services.\n\nImplement data orchestration and workflow automation using appropriate tools.\n\nWork with distributed processing technologies such as Spark and PySpark where required.\n\nSupport data warehousing, data lakes and lakehouse architectures.\n\nImplement data quality rules, exception handling and source-to-target reconciliation.\n\nApply data security, access control, encryption and privacy practices.\n\nImplement logging, monitoring, alerting and data observability.\n\nContribute to Git-based version control, CI/CD and automated deployment pipelines.\n\nDevelop and maintain unit, integration, regression and reconciliation tests.\n\nTroubleshoot production incidents, conduct root-cause analysis and support operational recovery.\n\nMaintain technical documentation, data mappings, designs and operational runbooks.\n\nCollaborate with software engineers, data engineers and business stakeholders.\n\nRequirements\nNon-Negotiable Requirements\nRelevant banking or financial services experience.\n\nStrong hands-on Data Engineering experience.\n\nAdvanced SQL engineering, including query optimisation, CTEs, window functions and query plans.\n\nStrong Python engineering, including reusable modules, libraries and testing.\n\nPractical ETL/ELT, data ingestion and transformation experience.\n\nData modelling experience across relational, dimensional or analytical models.\n\nCloud data engineering experience, with AWS as the core platform requirement.\n\nExperience with data quality, validation and reconciliation.\n\nKnowledge of data security, access control and privacy.\n\nFamiliarity with Git, CI/CD, automated testing and production support.\n\nStrong troubleshooting, problem-solving and technical documentation skills.\n\nAbility to work independently and take ownership of deliverables.\n\nExcellent communication and stakeholder management skills.\n\nAvailability to work onsite in Rosebank approximately 3 days per week.\n\nAvailability to commence on 1 January 2027.\n\nCore Technical Skills\nAWS\n\nAdvanced SQL\n\nPython\n\nETL/ELT\n\nData ingestion and transformation\n\nData modelling\n\nData quality and reconciliation\n\nData orchestration\n\nGit and CI/CD\n\nAutomated testing\n\nMonitoring and production support\n\nRole-Critical Technologies\nAWS S3, Glue, Lambda, Athena, Redshift and EMR.\n\nSpark and PySpark.\n\nKafka and event-driven processing.\n\nData warehousing, data lakes and lakehouse engineering.\n\nDelta Lake and medallion architecture patterns.\n\nSQS, SNS and EventBridge.\n\nAirflow/MWAA and Step Functions.\n\nTerraform and Infrastructure as Code.\n\nMetadata, data catalogues and lineage.\n\nPerformance optimisation, partitioning and query tuning.\n\nDesirable Capabilities\nBatch processing and workflow scheduling.\n\nData governance and data classification.\n\nCloud cost optimisation and FinOps awareness.\n\nLegacy ETL modernisation and cloud migration.\n\nData products, interfaces and service-level agreements/objectives.\n\nData mesh and federated governance.\n\nCore Attributes\nStrong banking or financial services awareness.\n\nSelf-starter who requires minimal supervision.\n\nTakes ownership of responsibilities and deliverables.\n\nProactive and analytical problem-solver.\n\nExcellent written and verbal communication.\n\nStrong attention to detail and data quality.\n\nProfessional stakeholder engagement.\n\nSmart and professional presentation appropriate to a banking environment.\n\nRecruitment priority: A strong, hands-on Data Engineer with banking experience, advanced SQL and Python capability, AWS expertise and a proven ability to deliver reliable data solutions independently.","description_format":"text","description_chars":5099,"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":["Financial 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