{"id":3109178,"url":"https://alion.io/job/intellect-design-arena-head-data-engineering","title":"Head Data Engineering","company":{"id":9200,"name":"Intellect Design Arena","domain":"intellectdesign.com","url":"https://alion.io/company/intellect-design-arena","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":29000,"max_usd":63000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":143},"experience_years_min":20,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false}],"status":"live","first_seen_at":"2026-10-22T17:36:40Z","employer_posted_date":null,"last_verified_at":"2026-10-22T17:36:40Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Location : Chennai / Hyderabad\n\nDomain: Wealth Management / Asset Management\n\nRole Overview\n\nWe are seeking an experienced Head of Data Engineering / Data Practice Head to build and lead the data engineering practice for Wealth Management and Asset Management platforms. The role will own the data strategy, engineering capabilities, architecture, delivery standards, and modernization of enterprise data platforms supporting investment, portfolio, client, and regulatory use cases.\n\nThe ideal candidate will combine strong data engineering leadership and technology expertise with deep understanding of Wealth/Asset Management data, investment processes, and financial products.\n\nKey Responsibilities\n\nData Practice Leadership\nBuild and lead a high-performing Data Engineering practice covering architecture, engineering, platform, governance, and delivery.\nDefine the data engineering strategy, technology roadmap, standards, and best practices aligned to business objectives.\nBuild engineering capabilities, talent strategy, operating models, and delivery practices across the data organization.\n\nData Engineering & Platform\nLead the design and modernization of scalable enterprise data platforms, data lakes/lakehouses, warehouses, and real-time data pipelines.\nDrive adoption of modern cloud data technologies, distributed processing, APIs, streaming, and data integration frameworks.\nEstablish standards for data quality, lineage, observability, security, scalability, and performance.\nPartner with Architecture, Product, Engineering, and Business teams to develop reusable data capabilities and platforms.\n\nWealth & Asset Management Domain\nBring strong understanding of investment management, portfolio management, wealth management, asset management, securities, performance, risk, and client data.\nDrive data solutions across areas such as portfolio analytics, investment reporting, client insights, performance measurement, risk, and regulatory reporting.\nUnderstand data across the investment lifecycle, including orders, trades, positions, holdings, pricing, corporate actions, benchmarks, and performance.\n\nData & AI Enablement\nBuild data foundations that enable advanced analytics, AI/ML, GenAI, and intelligent automation use cases.\nPartner with Data Science, AI, and Product teams to make high-quality, governed data readily accessible for analytics and AI applications.\nEstablish practices for responsible and secure use of enterprise data.\n\nGovernance & Stakeholder Management\nEstablish strong data governance, quality, security, and compliance practices in partnership with relevant functions.\nWork closely with senior business, technology, product, and client stakeholders to define priorities and deliver measurable outcomes.\nDrive technology modernization, continuous improvement, and engineering excellence across the data practice.\n\nQualifications & Experience\n\n20+ years of experience in Data Engineering, Data Platforms, Data Architecture, or Technology, with significant leadership experience.\nStrong experience building and leading enterprise-scale Data Engineering practices and large engineering teams.\nDeep domain experience in Wealth Management, Asset Management, Investment Management, Capital Markets, or related financial services.\nStrong understanding of investment and wealth data, including portfolio, holdings, transactions, pricing, performance, risk, and client data.\nProven experience with modern cloud data platforms, data lakes/lakehouses, data warehouses, ETL/ELT, streaming, APIs, and distributed data processing.\nExperience with cloud platforms such as AWS, Azure, or GCP and modern data engineering ecosystems.\nStrong understanding of data governance, quality, lineage, security, and regulatory requirements within financial services.\nExperience enabling AI/ML and advanced analytics through scalable data platforms.\nStrong executive stakeholder management and experience working with global financial institutions.\nProven ability to build teams, define technology strategy, and scale a data engineering 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