{"id":3244120,"url":"https://alion.io/job/uniper-senior-data-engineer","title":"Senior Data Engineer","company":{"id":1763931,"name":"Uniper","domain":"uniper.energy","url":"https://alion.io/company/uniper","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"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":21000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Iceberg","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Azure","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Collibra","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"Flink","optional":false},{"name":"Git","optional":false},{"name":"GraphQL","optional":false},{"name":"gRPC","optional":false},{"name":"Java","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"TimescaleDB","optional":false},{"name":"WebSockets","optional":false},{"name":"AI Agents","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-25T18:35:30Z","employer_posted_date":null,"last_verified_at":"2026-10-25T18:35:30Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"As the (Senior) Data/DataOps Engineer, you will be responsible for designing, developing, and maintaining scalable data pipelines, managing data integration, and ensuring robust data quality and governance to enhance and support our systematic trading activities. This role is critical to ensuring the efficiency, reliability, and scalability of our core data infrastructure, directly supporting our strategic trading initiatives. The ideal candidate has a passion for creating high-quality software, loves working with data in all its forms and shapes, enjoys solving complex problems, brings expertise in time series data and is adept at working with modern data platforms and tools.\n\nResponsibilities: \nGain a deep understanding of data requirements related to Uniper's energy trading business and translate them into technical designs.\nDesign, develop, and maintain scalable data pipelines for both batch and streaming data, ensuring data quality and consistency to support data analytics initiatives.\nDevelop and maintain robust data models that optimally support workloads of Uniper's analysts and traders, ensuring data is well structured and easily accessible.\nSeamlessly integrate market and other data from various sources, including internal and external data feeds, APIs, databases, and streaming services.\nImplement data quality checks, validation processes, and monitoring solutions; maintain data governance and security standards across all data domains.\nManage and maintain an up-to-date data catalogue using tools like Collibra to ensure metadata is accurately documented and accessible.\nDevelop and implement automation scripts and workflows to enhance efficiency and reduce manual intervention in data processing.\nMonitor and optimise the performance of data pipelines, ensuring efficient data processing and minimising disruptions.\nCollaborate cross-functionally with traders, analysts, software engineers, and other stakeholders to understand data requirements and ensure that solutions are aligned with business needs.\nLeverage tools and platforms, including Azure Databricks (utilising Unity Catalogue & Delta Lake), Snowflake, PostgreSQL, TimescaleDB, Kafka, and Flink, with a strong focus on time series data.\nStay updated on and experiment with emerging technologies like Delta Lake and Apache Iceberg to continuously enhance our Lakehouse architecture.\n\nRequirements: \nBachelor's or Master's degree in Computer Science, Mathematics, Engineering, or a related quantitative discipline.\n5+ years of proven expertise in Data/DataOps Engineering or related roles.\nStrong knowledge of software engineering best practices, object-oriented concepts, and the ins and outs of data-focused development.\nExpertise in utilising (and implementing) various API types, including REST, GraphQL, WebSocket, and gRPC.\nProficiency in Python, SQL, and data processing frameworks like Apache Spark.\nProficiency in Git and version control systems.\nExperience with cloud platforms (e. g., Azure) and tools like Databricks, Snowflake, PostgreSQL, and Kafka.\nExperience with Docker and containerization technologies.\nExpertise in handling both event-based and aggregated time series data.\nStrong understanding of modern data governance frameworks, data modelling, data architecture, OLAP & OLTP systems and their application in dynamic environments.\nPrevious experience in an operational data team, preferably in energy trading or a related field.\nExperience with DevOps techniques, including CI/CD and infrastructure-as-code.\nProficiency in at least one OOP language other than Python (e. g., Java, C#).\nExperience with Delta Live Tables (DLT) and/or dbt is a plus.\nExperience with web scraping techniques.\nFamiliarity with data cataloguing and quality monitoring solutions (e. g., Collibra).\nExperience in building Generative AI (GenAI) solutions, such as Retrieval-Augmented Generation (RAG) and Agentic AI.\nExcellent communication and collaboration skills to work effectively with technical teams and business stakeholders.\nStrong analytical thinking and problem-solving abilities.\nDemonstrated a high level of initiative, self-motivation, and a proactive, self-starter mindset, with a strong drive to independently identify and solve challenges.\nA passion for continuous learning, innovation, knowledge sharing, and driving excellence in data engineering.\nAbility to work effectively in a cross-functional, fast-paced environment.\n\nAdditional Requirements: \nFluency in English (verbal and written).\nSkills\napache spark, python, spark, sql","description_format":"text","description_chars":4545,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Nuclear Energy","Fossil Fuels","Hydroelectric","Oil & Gas"],"lifecycle":[{"event":"open","at":"2026-10-25T18:35:30Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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