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Ref: #73662
Senior Data Engineer
Senior Data Engineer (Architect + Hands-on Developer)
The opportunity
We are seeking a Senior Data Engineer (5+ years’ experience) who can operate at the intersection of solution architecture and hands-on development. This role requires an individual who can design scalable data architectures while actively building and maintaining production-grade data pipelines.
The core purpose is to architect, build, and optimize robust data platforms and pipelines that enable advanced analytics, business intelligence, and data-driven decision-making across the organization.
Your key responsibilities
- Architect and Design scalable, reliable, and cost-effective data platforms and pipelines aligned with business needs
- Develop and implement high-quality data pipelines to process large-scale structured and unstructured data
- Own end-to-end data lifecycle, including ingestion, transformation, storage, and consumption layers
- Establish data architecture standards, best practices, and reusable frameworks
- Optimize performance and cost of data systems across cloud platforms
- Ensure data quality, governance, security, and compliance across all data assets
- Provide technical leadership and guidance to junior engineers and collaborate with cross-functional teams
- Partner with stakeholders to translate business requirements into scalable technical solutions
- Troubleshoot production issues and ensure high availability and reliability of data systems
Skills and attributes for success
- Strong Engineering & Architectural Mindset: Ability to design scalable data solutions while staying hands-on with implementation
- Technical Depth in Python: Expertise in writing clean, modular, and production-ready code
- Modern Data Stack Expertise: Experience with platforms like Databricks, Spark, and distributed data processing systems
- Data Architecture Knowledge: Strong understanding of data lakes, lakehouses, and warehouse architectures and when to use each
- Cloud Expertise: Hands-on experience designing data solutions on AWS, Azure, or GCP
- Problem-Solving & Leadership: Ability to break down complex problems, guide teams, and drive technical decisions
- Collaboration Skills: Strong communication skills to work across technical and business stakeholders
To qualify for the role, you must have
- 5+ years of experience in Data Engineering with a mix of design/architecture and hands-on development
- Expert-level Python skills in building scalable data pipelines in production environments
- Strong experience with PySpark and distributed data processing frameworks
- Workflow orchestration expertise (Apache Airflow, Prefect, or similar)
- Advanced SQL skills with experience across relational and NoSQL databases
- Cloud platform experience (AWS, Azure, or GCP) with data services
- Experience in designing data architectures (data lakes, lakehouse, medallion architecture, etc.)
- Strong understanding of CI/CD, version control (Git), and DevOps practices for data pipelines
Ideally, you’ll also have
- Experience designing end-to-end enterprise data platforms
- Advanced Databricks capabilities including Delta Lake, MLflow, and performance tuning
- Exposure to data governance frameworks and data quality tools
- Knowledge of data modelling techniques (dimensional and normalized models)
- Familiarity with data science and machine learning pipelines
- Contributions to open-source projects or internal accelerators/frameworks
- Bachelor’s or master’s degree in computer science, Engineering, or related field
What we look for
We are looking for someone who:
- Can balance architecture thinking with hands-on execution
- Has a proven track record of building and scaling production data systems
- Takes ownership of technical decisions and system design
- Can mentor and uplift team members
- Communicates effectively with both technical and non-technical stakeholders
- Is proactive in adopting modern data technologies and best practices
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