{"id":3920880,"url":"https://alion.io/job/hcltech-azure-data-technical-specialist-13","title":"Azure Data Technical Specialist","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","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":["Amberpet, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Jenkins","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scrum","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Machine Learning","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-07T14:54:34Z","employer_posted_date":"2026-11-07","last_verified_at":"2026-11-08T05:32:14Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Job Summary\n\nYour Role:\nAs the Senior Data Engineer in the Data Foundation scope, you have in-depth knowledge of the technical details and how the products work, and you will act as an expert in the team responsible for the technical configuration, development and integration of products and platforms based on our tech stack, used by specific business processes across OpCos, to better serve their customers.\nYou will provide expert guidance and ensure alignment with architecture and business objectives and ensure on-time delivery. You drive the end-to-end operations of the platforms, keeping them streamlined, structured, and within service level agreements.\nYou will collaborate closely with other cross functional teams for efficient development pipelines.\nYou will work directly with the Product Owner(s) and Product Architect(s), receiving pre-defined business requirements and translating them into technical specifications and services in line with overall engineering standards and roadmaps.\nYou will be expected to be implementing new features, deliver high quality code, follow the agile methodologies and be a team player. The most important part is to be part of the team effort towards value-driven outcomes and the successful completion of tasks. Your proactive approach will be key in maintaining comprehensive documentation and collaborating with your team members through offering help, raising question and actively taking part in all activities.\nYou will serve as a key contributor in refining and driving excellence in engineering practices to deliver high-quality solutions throughout the software development lifecycle in our Data landscape.\nThe role reports directly to the Data Engineering Lead\n\nKey Responsibilities\n\nYour responsibilities will include:\nCoach and mentor individual Data Engineers in designing, developing, and delivering scalable, reliable, and high performing big data solutions\nCoach and mentor the design, development, and maintenance of scalable data pipelines and ETL processes. Monitor and optimize data infrastructure performance, identifying and resolving bottlenecks and issues.\nCoach and mentor the team from a technical standpoint, and drive operational excellence, including code reviews, design reviews, testing, and deployment processes.\nBe an individual contributor (~60%) engineering the software products/solutions, jointly with the team\nEnsure that the team adheres to coding standards, best practices, and architectural guidelines, oversee team spirit and team performance, guide and mentor team members.\nOversee the implementation of the technical architecture, solve immediate technical challenges.\nEnsure that the execution of DevSecOps is in place in the team's daily work\nInspire, advise, and drive the selection of development approach.\nCoordinate software development and address technical debt in the team\nSupport onboarding, mentor, and develop top engineering talents, fostering a culture of learning,\ncollaboration, and continuous improvement.\nTake Lead when needed in technical discussions with other teams/departments and oversees state-of-art quality of the stack.\nMay be involved in cross-functional discussions, representing the domain in broader technical discussions across domains.\nResponsible for designing and improving processes that enhance efficiency and quality.\nCommunication with Engineering Manager, Product Owner and Scrum Master to align on project / sprint goals, timeline and resource allocation.\n\nSkill Requirements\nMust have (all levels):\nProficiency in programming languages such as Python, SQL, and experience with big data technologies like Massive Parallel Processing (MPP) and streaming.\nExperience with cloud platforms (e.g., AWS, Azure, GCP) and compute/data storage solutions (e.g., Databricks, BigQuery, Snowflake).\nExperience with CI/CD processes and tools, including Azure DevOps, Jenkins, and Git, to ensure smooth and efficient deployment of data solutions.\nFamiliarity with APIs to push and pull data from data systems and Platforms.\nFamiliarity with understanding software architecture High level Design document and translating them to developmental tasks.\nExpert in Pyspark \nFamiliarity with Microsoft data stack such as Azure Data Factory, Azure Synapse, Databricks and Fabric / PowerBI.\nApache Kafka or similar\nData Modelling & Architecture\nETL pipeline design\nNice to have:\nLogging and Monitoring using Azure / Databricks services\nExperience with machine learning and AI technologies\n\nYou are a good match if you have:\n8+ years of experience in Data Engineering, with a strong understanding of data integration, ETL processes, and data warehousing.\nHands-on experience and in-depth knowledge of the technologies listed as mandatory in the Technology Stack section\nStrong understanding and implementation of software development principles, coding standards, and modern architecture\nFamiliarity with data governance and compliance standards.\nHands-on experience in implementing and managing End-to-End DataOps / Data Engineering projects in a team\nProven ability to lead software development teams of engineers with varying experience and adapt to team sizes from small to large\nExperience in working in diverse projects with varying technologies, products, and systems\n Strong problem-solving skills and ability to make critical technical decisions\nAbility to guide / mentor other team members\nEffective communication and interpersonal skills, with the ability to collaborate with technical and non-technical stakeholders.\nProven ability to demonstrate that can work independently and a self-starter\nPragmatic, and collaborative team player\n\nOther Requirements\nExcellent written and verbal English\nOther language required to perform job for the given 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