{"id":4057840,"url":"https://alion.io/job/symphoni-hr-technical-delivery-manager","title":"Technical Delivery Manager","company":{"id":3800108,"name":"Symphoni HR","domain":"symphonihr.com","url":"https://alion.io/company/symphoni-hr","size_band":"201-500","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"A","score":93,"open_postings":43,"ghost_share":0,"stale_share":0,"repost_share":0.465,"time_to_fill_p50_days":45,"computed_at":"2026-11-11T05:49:22Z"}},"role":"Product","role_family":"Product","seniority":"lead","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":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-11T06:21:12Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T06:21:56Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"The Technical Delivery Manager will provide technical leadership across data engineering, cloud, AI-enabled data solutions, and enterprise data platform initiatives. The role combines hands-on solution design with team leadership, mentoring, and client engagement to drive high-quality delivery. You will work closely with clients, architects, product owners, and governance teams to shape scalable, secure, and compliant data architectures.\nOur client is a leading global organisation in the computer software industry, delivering data and technology solutions at enterprise scale. They serve large financial services and capital markets clients through modern cloud and data platforms. The culture emphasises engineering excellence, continuous learning, and trusted client relationships.\nResponsibilities\nProvide technical leadership across data engineering, cloud, AI, and enterprise data platform initiatives.\nLead, manage, mentor, and guide engineering teams to ensure high-quality delivery and continuous capability development.\nEngage clients by understanding business priorities, managing expectations, and communicating technical solutions clearly.\nDesign and review scalable, secure, and cost-effective data architectures, data models, lakehouse platforms, and cloud-based data solutions.\nDrive data cataloging, metadata management, data governance, data quality, and compliance practices across enterprise data platforms.\nEvaluate and implement AI/ML-enabled features and automation to improve platform efficiency and business outcomes.\nChampion best practices in data engineering, cloud, DevOps, CI/CD, performance optimisation, and engineering excellence.\nParticipate in technical assessments, solution reviews, interviews, and capability-building initiatives for data engineering roles.\nRequirements\n12+ years of overall experience in data engineering, data platforms, cloud technologies, AI-enabled data solutions, and enterprise architecture.\n4+ years in a technical leadership role, including team management, mentoring, delivery ownership, and stakeholder collaboration.\nStrong hands-on expertise in Databricks and Snowflake, with experience on AWS, Azure, or GCP.\nStrong knowledge of Spark, PySpark, Python, SQL, and large-scale data processing frameworks.\nExperience in data modelling, data cataloguing, metadata management, data governance, and enterprise data management.\nExperience building data lakes, data warehouses, lakehouse platforms, ETL/ELT pipelines, and orchestration workflows.\nUnderstanding of AI/ML concepts, GenAI-enabled data solutions, and AI-driven engineering practices.\nPreferred: experience in Banking and Capital Markets or Financial Services, and exposure to data security and regulatory compliance.\nSkills\nDatabricks, Snowflake, AWS, Azure, or GCP, Spark, PySpark, Python, SQL, Data Modeling, Data Cataloging, Data Governance, Data Lakes, Data Warehouses, Lakehouse Platforms, ETL/ELT Pipelines, Orchestration Workflows, AI/ML Concepts, GenAI-enabled Data Solutions, DevOps, CI/CD, Banking and Capital Markets / Financial Services domain, Data Security, Regulatory Compliance","description_format":"text","description_chars":3121,"description_truncated":false,"requirements":{"experience_years_min":12,"management_years_min":4,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-11-11T06:21:12Z"}],"visa":[],"liveness":{"score":52,"band":"ok","label":"Likely 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