Qode
FinTech, BFSI, Digital Startups
DataEngineeringLead/SeniorDataEngineer
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“Data Engineering Lead / Senior Data Engineer at Qode. Skills: Data Engineering, Cloud Platforms (AWS preferred), Data Modeling, ETL/ELT Pipelines, SQL, Python, Leadership. Lead data engineering initiatives. Shape data models and analytics foundations”
What You'll Achieve.
data drives business decisions and analytics; deliver impactful cloud solutions
Industry & Context.
What They're Looking For.
Must Have
7+ years of experience in data engineering or related roles, hands-on data engineer (ETL, data modeling, analytics datasets), Experience designing data models for analytics and reporting, not just raw ingestion, Proficient in SQL, Proficient in Python, Hands-on experience with cloud platforms (AWS preferred ; GCP/Azure acceptable), Experience with orchestration and transformation tools (Airflow, DBT, Glue, etc.), team leadership skills, experience working directly with business stakeholders (e.g. Finance, Risk, Sales, Marketing, Operations) to gather data or analytics requirements
Nice to Have
Experience working with BI or Analytics teams (Looker, Power BI, Tableau, etc.), Exposure to AI/ML data pipelines or analytics use cases, Consulting or customer-facing experience, Cloud certifications (AWS Data Analytics, Solutions Architect, etc.)
What You'll Do.
Lead data engineering initiatives
Shape data models and analytics foundations
Own the design of analytics-ready data models aligned with business KPIs and use cases
Translate business and customer requirements into scalable data solutions
and Business teams to define metrics
Participating in and building modern cloud-based data platforms (Data Lake
Develop and maintain robust ETL/ELT pipelines using tools such as Airflow
and performance across pipelines and datasets
Support real-time or near–real-time data processing when required
Lead and mentor data engineers
providing technical guidance and code reviews
Act as a technical point of contact for customers
explaining data solutions and trade-offs
Collaborate with Cloud Architects
and AI teams to deliver end-to-end solutions
Contribute to project planning
and delivery ownership
How You'll Work.
Team & Collaboration
Work closely with business stakeholders and customers; Partner with Product, Analytics, and Business teams; Collaborate with Cloud Architects, DevOps, and AI teams
Communication Scope
explaining data solutions and trade-offs
Process & Methodology
Contribute to project planning, estimation, and delivery ownership
Full Job Description
_This is a position we're hiring for on behalf of our client._ **🚀 Company Introduction** Our client empowers organizations by transitioning legacy workloads to cutting-edge Cloud, DevOps, and AI technologies. As**Vietnam's AWS Partner of the Year** for two years in a row, they bring deep expertise and innovative thinking to every project. They're not just a consultancy, they're a transformation partner. Their dynamic team of engineers, architects, and DevOps experts is passionate about delivering impactful cloud solutions across industries, including FinTech, BFSI, and Digital Startups. **🧠 About the Role** We are looking for an experienced **Data Engineering Lead / Senior Data Engineer** who goes beyond building pipelines and understands how data drives **business decisions and analytics**. In this role, you will: * Lead data engineering initiatives * Shape data models and analytics foundations * Work closely with business stakeholders and customers * Guide a team of data engineers This role is ideal for someone who is ready to step up, take the lead, and own both the technical and business-facing aspects of a fast-growing data practice. **📌 Key Responsibilities** ### **Data & Analytics Leadership** Own the design of **analytics-ready data models** aligned with business KPIs and use cases. Translate business and customer requirements into scalable data solutions. Partner with Product, Analytics, and Business teams to define metrics, reporting structures, and data standards. **Data Engineering & Architecture** Participating in and building modern **cloud-based data platforms** (Data Lake, Data Warehouse, Lakehouse). Develop and maintain robust **ETL/ELT pipelines** using tools such as Airflow, DBT, Glue, Spark, etc. Ensure data quality, reliability, and performance across pipelines and datasets. Support real-time or near–real-time data processing when required. **Leadership & Stakeholder Engagement** Lead and mentor data engineers, providing technical guidance a
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