Lead Data Engineer

At the time of application, candidates must be Vietnam citizens

Lead data engineers at Thoughtworks develop modern data architecture approaches to meet key business objectives and provide end-to-end data solutions. They might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems. On projects, they will be leading the design of technical solutions, or perhaps overseeing a program inception to build a new product. Alongside hands-on coding, they are leading the team to implement the solution.

• You will lead and manage data engineering projects from inception to completion, including goal-setting, scope definition and ensuring on-time delivery with cross team collaboration.
• You will collaborate with stakeholders to understand their strategic objectives and identify opportunities to leverage data and data quality.
• You will design, develop and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions.
• You will be responsible to create, design and develop intricate data processing pipelines, addressing clients' most challenging problems.
• You will collaborate with data scientists to design scalable implementations of their models.
• You write clean and iterative code based on TDD and leverage various continuous delivery practices to deploy, support and operate data pipelines.
• You will lead and advise clients on how to use different distributed storage and computing technologies from the plethora of options available.
• You will develop data models by selecting from a variety of modeling techniques and implementing the chosen data model using the appropriate technology stack.
• You will be responsible for data governance, data security and data privacy to support business and compliance requirements.
• You will define the strategy for and incorporate data quality into your day-to-day work.

• Expert-level Databricks skills (SparkSQL, PySpark, Spark DataFrames) and open table formats (Delta Lake, Apache Iceberg).
• Deep expertise in columnar storage formats, advanced performance tuning, and optimization strategies (Parquet, ORC, Z-Order, clustering).
• Ability to define, architect, and implement modern data architecture patterns (Medallion, data mesh, data product approach).
• Mastery of dbt (core/cloud) and advanced SQL for complex analytical transformations, including performance optimization. Expertise in establishing and enforcing data quality, testing, and governance frameworks (Great Expectations, dbt tests, data contracts).
• Extensive experience designing and implementing highly scalable streaming and batch data ingestion frameworks (Kafka, Autoloader, APIs, SFTP) and data/file formats (CSV, JSON, YAML).
• Experience with event-driven architectures (AWS EventBridge, GCP Pub/Sub, Azure Event Grid).
• Architect-level cloud platform expertise (AWS, GCP, or Azure) with deep experience in multiple warehouses (BigQuery, Redshift, Synapse). Knowledge and implementation of security and compliance in cloud data environments (RBAC, data masking, encryption, GDPR/CCPA) and implementation of cost optimization strategies for cloud data platforms.
• Leadership in defining and implementing DevOps & infrastructure-as-code strategies (GitLab/GitHub CI/CD, Terraform). Proven ability to design and implement comprehensive observability & monitoring solutions (logging, alerting, pipeline performance tracking).
• Leadership in defining and implementing DevOps & infrastructure-as-code strategies (GitLab/GitHub CI/CD, Terraform). Proven ability to design and implement comprehensive observability & monitoring solutions (logging, alerting, pipeline performance tracking).
• Expert Python engineering skills, leading best practices in software engineering (version control, modularity, testing).

• Demonstrated experience in leading large data teams, driving collaboration with business, analysts, and data scientists, and influencing technical direction.
• Proven ability in data product design and domain-driven design in data platforms.
• Solid experience with machine learning pipelines and MLOps (MLflow, Vertex AI, SageMaker, Azure ML).
• Hands-on experience with real-time analytics and low-latency serving layers (e.g., Apache Flink, Materialize, Rockset).
• Practical experience with vector databases (Pinecone, Weaviate, ChromaDB) or semantic search in AI workflows.

There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.

Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we're pushing boundaries through our purposeful and impactful work. For 30+ years, we've delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let's be extraordinary.

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