Senior Data Engineer

Role Overview

The Senior Data Engineer is responsible for bridging business objectives and technical execution, leading the delivery of data engineering initiatives spanning data lakes, data platform modernization, and reporting solutions. The role requires strong expertise in cloud data architectures and hands-on delivery experience, combined with the ability to collaborate effectively with business and technology stakeholders.

Key responsibilities include translating business requirements into technical solutions, defining project scope, estimating delivery effort, managing timelines, and decomposing complex solution designs into executable engineering tasks.

Position Responsibilities:

Partner closely with business unit leaders, product owners, and IT stakeholders to capture business requirements, define project scopes, and establish clear delivery timelines.

Perform workload and effort estimation; break down complex data initiatives into detailed technical epics, user stories, and execution roadmaps.

Drive project delivery from architecture design through to testing, deployment, and operational handoff while proactively managing risks, dependencies, and scope creep.

Serve as the primary technical interface between business stakeholders and the data engineering team, translating business needs into high-performing data solutions.

Design, build, and optimize scalable batch and real-time data pipelines, data lakehouse architectures, and data warehousing solutions.

Provide technical leadership for enterprise data platforms, driving architecture, engineering best practices, platform optimization, and innovation across Azure Cloud, Databricks (Spark), DataWorks, MaxCompute, OSS, and Hologres.

Implement robust data orchestration, data ingestion, cleansing, transformation, augmentation, and data quality control processes.

Establish and enforce technical quality standards, data governance frameworks, and best practices across data ingestion, storage, and processing.

Conduct thorough code reviews, lead technical troubleshooting, and ensure data pipelines are secure, resilient, and cost-optimized.

Mentor and coach mid/junior data engineers, fostering a collaborative, continuous-learning environment.

Required Qualifications:

Bachelor’s or Master’s degree in Computer Science, Information Systems, Quantitative Engineering, or a related field.

Minimum 10+ years of IT experience, with at least 3+ years specifically in data engineering delivery leadership or technical lead roles.

Solid domain understanding of the Insurance or Financial Services industry (e.g., policy administration, claims management, actuarial metrics, agency analytics).

Proven track record in delivery leadership—demonstrated ability in effort estimation, scope decomposition, sprint planning, and managing cross-functional stakeholder expectations.

Hands-on experience with Azure Cloud Services (Azure Data Lake Storage, Azure Data Factory, Azure SQL/Synapse) and database technology (Oracle, SQL Server, or PostgreSQL).

Strong proficiency with Azure Databricks, Apache Spark (PySpark / Spark SQL), and modern ETL/ELT pipeline design.

Deep expertise in enterprise data design methodologies, dimensional modeling (Kimball), data lakehouse architecture, and data warehousing concepts.

Excellent verbal and written communication skills with the ability to articulate technical visions, architectural trade-offs, and project updates to non-technical stakeholders.

Practical experience or familiarity with AliCloud big data tools, specifically DataWorks, MaxCompute, OSS, and Hologres.

Experience with FineBI, Power BI, or similar enterprise reporting tools

When you join our team:

We’ll empower you to learn and grow the career you want.

We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.

As part of our global team, we’ll support you in shaping the future you want to see.

宏利金融有限公司是全球领先的金融服务提供商，致力于帮助大众轻松作出明智抉择，实现精彩人生。如欲了解更多关于我们的信息，请访问人寿保险-养老保险-健康保险-中宏保险官网 (manulife-sinochem.com).

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Working Arrangement

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