We are seeking a Data Engineer with 4+ years of experience to join our Cloud Data & Engineering team. The ideal candidate has strong expertise in building scalable, cloud-native data platforms and is passionate about solving complex data challenges. This role involves working across platform development and data migration initiatives to deliver efficient, high-impact solutions.
In this role, you will design, build, and optimize modern cloud data architectures, including data pipelines, real-time and batch processing systems, and large-scale migration efforts. You will collaborate with cross-functional teams to deliver secure, high-performing, and cost-effective data solutions using modern tools and best practices.
Roles & Responsibilities
- Design and build scalable, cloud-native data platforms and pipelines aligned with modern data lake/lakehouse architectures.
- Develop and optimize large-scale data processing solutions using frameworks such as Spark, PySpark, or equivalent technologies.
- Implement real-time and event-driven data ingestion pipelines to support dynamic business use cases.
- Lead and execute large-scale data migration and modernization initiatives, ensuring minimal disruption and optimal performance.
- Perform advanced query tuning, schema design, and performance optimization for relational databases.
- Develop automation frameworks and scripts to streamline data workflows, migration processes, and operational tasks.
- Implement Infrastructure-as-Code (IaC) and integrate CI/CD pipelines to enable efficient and reliable deployments.
- Ensure adherence to cloud security best practices, along with implementing HA/DR strategies and cost optimization techniques.
- Work closely with engineering, product, and customer teams to deliver scalable, high-quality data solutions.
Requirements
Requirements
Qualifications & Skills
- Bachelor's degree in Computer Science, Engineering, or a related technical field
- 4+ years of experience in Data Engineering or Database Engineering
- 2+ years of experience delivering cloud-based data solutions
- Strong expertise in building cloud-native data platforms and pipelines
- Deep understanding of modern data lake/lakehouse architectures
- Hands-on experience with distributed processing frameworks (Spark, PySpark, or equivalent)
- Experience with streaming or event-driven data ingestion patterns
- Strong proficiency in Python with solid engineering principles (OOP, testing, clean coding)
- Expertise in relational databases, schema design, and query optimization
- Experience executing large-scale data migration and modernization projects
- Knowledge of high availability (HA), disaster recovery (DR), and cloud security best practices
- Experience with Infrastructure-as-Code (IaC) and CI/CD pipeline integration
- Strong understanding of cost optimization and performance tuning in cloud environments
- Excellent problem-solving, communication, and collaboration skills
- Experience working in a fast-paced, client-facing or consulting environment is preferred
Signs You May Be a Great Fit
- Impact: Play a key role in building modern, scalable data platforms that enable data-driven decision-making for customers.
- Ownership: Take end-to-end responsibility for data solutions, from design to deployment and optimization.
- Growth: Work with cutting-edge cloud and data technologies while continuously enhancing your technical expertise.
- Culture: Thrive in a collaborative, fast-paced environment that values innovation, accountability, and continuous learning.
