{"id":2001686,"url":"https://alion.io/job/bp-enterprise-technology-engineer","title":"Enterprise Technology Engineer","company":{"id":2557,"name":"BP","domain":"bp.com","url":"https://alion.io/company/bp-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","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":{"min_usd":17500,"max_usd":36000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":10},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"Kanban","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Pandas","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Scrum","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Terraform","optional":false},{"name":"Azure","optional":true}],"status":"live","first_seen_at":"2026-10-07T11:43:20Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-12T02:28:57Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Entity:\nTechnologyJob Family Group:\nIT&S GroupJob Description:\nEnterprise Tech Engineer - Data Engineering\nDigital Trading Analytics | Trading Analytics & Insights (TA&I)\nAt bp, our people are our most valuable asset. The Technology DS&C, People, Culture & Communications (PC&C) function fosters a diverse, inclusive culture where everybody can thrive. As we transition from an oil company to an integrated energy company, we are embarking on a major transformation to be more competitive, responsive, and customer-focused.\nWe’re investing in key locations such as India, Hungary, Malaysia, and Brazil, offering an exciting but challenging opportunity to shape a fast-moving PC&C function, building teams and structures and driving continuous improvement.\nWe’re looking for driven, ambitious enthusiasts who thrive in fast-paced environments and are passionate about people. If you're ready to build something transformative, this is the place for you.\nThe Global Solution Owner Automation and AI is responsible for owning the products, architecture, vendor relationships, and compliance globally.\nYou will work with\nYou will join Digital Trading Analytics and support the Trading Analytics & Insights (TA&I) organisation. We are a global, high-performing team that works closely with traders, trading analysts, business analysts, and engineers to turn data into useful insight for energy trading.\nYou will work in an Agile delivery environment using Kanban and Scrum practices. Azure DevOps is used to plan, track, and deliver work.\nAbout the role\nAs an Enterprise Tech Engineer - Data Engineering, you will design, build, and support scalable data pipelines for business intelligence and analytics platforms. You will ensure data is accurate, timely, secure, and easy to use across systems. Your work will directly support trading operations through reliable, high-quality data products.\nYou will also use approved AI-enabled engineering tools responsibly to improve coding speed, quality, documentation, and problem solving. This is not an AI research role; it requires practical AI fluency and sound engineering judgement.\nWhat you will deliver\nArchitect, design, and implement robust data pipelines using Python, Pandas, SQL, Apache Airflow, and Databricks. \nBuild and maintain ETL/ELT processes that ingest data from APIs, relational databases, event streams, and flat files. \nDevelop cloud-based data solutions using AWS services such as S3, EC2, EKS, IAM, Glue, and CloudWatch where appropriate. \nOptimise, monitor, and troubleshoot pipelines for performance, cost, resilience, and scalability. \nUse distributed processing technologies such as Spark/PySpark and Delta Lake for large-scale workloads. \nImplement data quality checks, lineage, observability, and clear operational runbooks. \nCreate clear data visualisations and technical communication for both technical and non-technical audiences. \nWork with multi-functional partners to translate trading and business needs into fit-for-purpose data solutions. \nApply Agile practices, version control, code review, automated testing, and release subject area. \nAI-enabled engineering and productivity\nYou will use approved AI tools to accelerate delivery while protecting company data, validating output, and retaining accountability for production decisions.\nUnderstand practical AI fundamentals, including how LLMs generate responses, common limitations, hallucinations, and privacy risks. \nUse coding assistants and AI tools effectively for code drafts, tests, documentation, SQL review, debugging, and knowledge discovery. \nWrite clear prompts: state the goal, constraints, inputs, expected output, and acceptance checks. \nCreate useful context for AI tools using relevant schemas, examples, business rules, and bounded source material without exposing critical information. \nUnderstand RAG fundamentals: document retrieval, grounding, citations, evaluation, and access control. \nEvaluate AI-generated work through testing, peer review, source checks, and security review before production use. \nKeep current with approved emerging AI capabilities and propose practical uses that improve productivity or data quality. \nWhat you will need to be successful\n3+ years of data engineering experience in an enterprise environment. \nStrong Python and Pandas skills, including HTTP/API integration (for example, Requests). Use web automation only where it is approved, lawful, and appropriate for the source. \nAdvanced SQL and solid understanding of relational data modelling and databases. \nProven ETL/ELT and pipeline design experience, including hands-on Apache Airflow. \nHands-on Databricks and distributed processing experience; Spark/PySpark and Delta Lake are strongly preferred. \nExperience building and operating data solutions on AWS, including S3 and relevant managed data services; familiarity with IAM is expected. \nExperience with EKS is helpful where workloads run on Kubernetes. \nExperience with messaging or streaming systems such as Kafka; familiarity with event-driven data patterns is helpful. \nSolid understanding of Linux, Git, pull-request workflows, and CI/CD. Azure DevOps experience is helpful. \nFamiliarity with Docker, infrastructure as code (for example Terraform, Jenkins), and secure cloud deployment practices. \nExperience with Tableau, Power BI, or similar visualisation tools. \nUnderstanding of secure engineering standards and documentation practices. \nBasic practical knowledge of LLMs, RAG, prompt design, context design, and safe use of AI developer tools. \nStrong analytical, problem-solving, communication, collaboration, and organisational skills. \nA responsible, self-motivated, adaptable approach and a genuine interest in automation. \nExperience in trading, financial services, energy, or another regulated data-intensive domain is advantageous. \nA Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience. \nWhy bp?\nAt bp, we support our people to learn and grow in a diverse and challenging environment. We believe that our team is strengthened by diversity. We are committed to crafting an inclusive environment in which everyone is respected and treated fairly. Diversity Statement: At bp, we provide an excellent environment and benefits such as an open and inclusive culture, a great work-life balance, tremendous learning and development opportunities to craft your career path, life and health insurance, medical care package and many others!\nDiversity sits at the heart of our company and as an equal opportunity employer, we stay true to our mission by ensuring that our place can be anyone's place. We do not discriminate based on race, religion, colour, national origin, gender and gender identity, sexual orientation, age, marital status, veteran status or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application and interview process, to perform essential job functions, and to receive other benefits and privileges of employment.\nTravel Requirement\nUp to 10% travel should be expected with this roleRelocation Assistance:\nThis role is eligible for relocation within countryRemote Type:\nThis position is a hybrid of office/remote workingSkills:\nAgility core practices, Agility core practices, API and platform design, Cloud Platforms, Collaboration, Communication, Configuration management and release, Continuous deployment and release, Creating a high performing team, Digital Project Management, Documentation and knowledge sharing, Emerging technology monitoring, Facilitation, Information Security, Mentoring, Metrics definition and instrumentation, NoSql data modelling, Problem Solving, Relational Data Modeling, Risk Management, Scripting, Secure development, Service operations and resiliency, Software Design and Development, Solution Architecture {+ 6 more}.\n\n Legal Disclaimer:\nWe are an equal opportunity employer. We do not discriminate on the basis of protected characteristics like race, religion, color, sex, national origin, sexual orientation, veteran status or disability status. Individualswith an accessibility need may request an adjustment/accommodationrelated to bp’s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodationrelated to the recruitment process, please contact us.\nIf you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. 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