Senior Data Engineer (Contract) [HR208] (PK)

Smart Working is dedicated to creating work experiences that feel right every day, not just look good on paper. This opportunity goes beyond typical remote roles by fostering a genuine community focused on your growth and well-being from day one. Our mission is to eliminate geographic barriers by connecting skilled professionals with exceptional global teams for full-time, long-term positions. We prioritize meaningful work where you can thrive personally and professionally, supported by one of the highest-rated remote-first workplaces on Glassdoor.

Key Responsibilities

- Architect and develop scalable data pipelines and infrastructure to support AI and product systems.
- Design and maintain data ingestion, transformation, and storage architectures for both operational and AI workloads.
- Build and manage batch and real-time data pipelines to ensure seamless data flow.
- Develop and optimize systems for vector search, retrieval, and machine learning data workflows.
- Ensure data reliability, security, and governance across the platform.
- Collaborate closely with AI, backend engineering, product, and leadership teams to support training, inference, and product features.
- Implement monitoring, observability, and data quality frameworks to maintain high data standards.
- Optimize performance for large-scale datasets and complex query systems.
- Contribute to technical architecture decisions and define long-term data strategy.
- Serve as the founding senior data engineer, establishing culture, standards, and hiring criteria for the growing data function.
- Partner directly with founders and product leadership to translate data capabilities into impactful product decisions.

Required Qualifications

- Over 7 years of professional experience, primarily in dedicated data engineering roles.
- Proven expertise in designing and building complex data pipelines and distributed data systems.
- Strong experience with relational databases, preferably PostgreSQL; MySQL or similar is acceptable.
- Hands-on experience with NoSQL databases.
- Familiarity with vector databases used in modern AI applications.
- Proficient programming skills in Python.
- Demonstrated ability to make and justify architectural decisions independently.
- Experience building scalable backend systems and designing data models and storage architectures.
- Deep understanding of data processing performance and optimization techniques.
- Experience with data frameworks and infrastructure technologies such as Apache Spark, Apache Airflow, Kafka, and Elasticsearch or OpenSearch is highly desirable.
- Knowledge of relevant database technologies including PostgreSQL, MongoDB, and vector databases like Qdrant, Milvus, or pgvector is advantageous.
- Experience with Python data-processing libraries such as Pandas or Polars is a plus.

Preferred Qualifications and Benefits

- Experience working on AI or machine learning platforms.
- Familiarity with stream processing and event-driven architectures.
- Exposure to cloud infrastructure platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure.
- Background in high-growth startups or early-stage companies is beneficial.

Please note that artificial intelligence tools may be used to assist in reviewing applications and assessing candidate materials during the hiring process. These tools support but do not replace human judgment, and all final hiring decisions are made by our recruitment team. For more information about data processing during recruitment, inquiries can be made through official company channels.